WO2016147899A1 - Device for hanger detection by image processing - Google Patents
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- WO2016147899A1 WO2016147899A1 PCT/JP2016/056715 JP2016056715W WO2016147899A1 WO 2016147899 A1 WO2016147899 A1 WO 2016147899A1 JP 2016056715 W JP2016056715 W JP 2016056715W WO 2016147899 A1 WO2016147899 A1 WO 2016147899A1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60M—POWER SUPPLY LINES, AND DEVICES ALONG RAILS, FOR ELECTRICALLY- PROPELLED VEHICLES
- B60M1/00—Power supply lines for contact with collector on vehicle
- B60M1/12—Trolley lines; Accessories therefor
- B60M1/28—Manufacturing or repairing trolley lines
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
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- the present invention relates to a hanger detection device by image processing that detects a hanger by image processing and detects a travel position of a train car and an angle abnormality of the hanger.
- a railway operator records a train track while traveling and specifies the traveling position of the train from the recorded image.
- GPS and ATC technologies for identifying the location of trains.
- these technologies are accurate enough not to interfere with train operation, but when train locations are identified from images. Therefore, it is required to grasp the traveling position more accurately.
- Patent Documents 1 and 2 are known as techniques for detecting hangers.
- Patent Document 1 is a patent that detects hangers from captured images by template matching processing or vertical edge detection processing.
- Patent Document 2 is a patent for detecting a hanger by detecting an intersection of two straight lines from a captured image by detecting a Hough transform process, a luminance histogram process, or two straight lines.
- Patent Documents 1 and 2 are capable of detecting hangers as long as they have a simple line configuration. However, as shown in FIG. It is difficult to detect the hanger 6 at a location where 5 intersects.
- Patent document 1 detects a hanger by vertical edge detection. In general edge detection, a portion having a large differential value between 2 pixels is detected as an edge. The local detection of 2 pixels has a problem with many false detections.
- Patent document 2 is a patent which detects a hanger by Hough transformation. The Hough transform finds a hanger using a relative vote amount between the feature of the entire image and the hanger feature, so it is difficult to detect the hanger 6 that appears small relative to the entire image as shown in FIG.
- Patent Document 3 As a related patent. This is an invention for measuring wear of a trolley wire, and is a patent for robustly detecting a worn portion of a trolley wire by removing the background by GSTH processing (see FIGS. 4 and 5).
- the GSTH process of Patent Document 3 is characterized in that the illumination light on the lower surface of the trolley wire is reflected in white. Since there is no part which reflects white in the hanger which is the object of this case, it is difficult to detect the hanger using Patent Document 3.
- an object of the present invention is to provide a hanger detection device using image processing that can detect a hanger with higher accuracy.
- a hanger detection device by image processing according to the first invention for solving the above-mentioned problems is A line sensor camera for photographing a hanger that is installed at equal intervals and supports a trolley line from the roof of the vehicle, and an image processing unit that is installed inside the vehicle and analyzes an image obtained by the line sensor camera, A hanger detection device by image processing for detecting a hanger in an image, The image processing unit A GSTH processing unit that sequentially performs GSTH processing on a line sensor image input from the line sensor camera in a shooting line direction and a time direction of the line sensor camera to obtain a GSTH image in which the hanger in the image is emphasized; , And a hanger detector for detecting a hanger from the GSTH image.
- the GSTH processing unit obtains a first GSTH image by performing an expansion process on the line sensor image after performing a contraction process on the imaging line direction of the line sensor camera as the GSTH process, and acquiring the first GSTH image.
- a difference image is obtained by taking a difference between the image and the first GSTH image, and after the shrinkage process is performed on the difference image in the time direction, the expansion process is performed to emphasize the hanger in the line sensor image Get a second GSTH image, The hanger detection unit detects the hanger from the second GSTH image.
- the GSTH processing unit obtains a gsth image by performing only a contraction process on the line sensor image in the photographing line direction of the line sensor camera, and acquires a gsth image in the time direction on the gsth image.
- the GSTH image in which the hanger in the line sensor image is emphasized by performing an expansion process after performing The hanger detection unit detects the hanger from the GSTH image.
- the hanger detection apparatus by the image processing which concerns on 4th invention is the invention in any one of 1st to 3rd.
- the GSTH processing unit inverts the luminance value for the line sensor image, one line at a time for the shooting line direction of the line sensor camera, and the luminance value of the main component in the shooting line direction when the luminance value of the main component is light color. When the value is a dark color, the GSTH process is performed after the luminance inversion process that does not invert the luminance value.
- FIG. 10 is a schematic diagram illustrating an example in which the image shown in FIG. 9 is subjected to GSTH processing in a region long in the x direction. It is a schematic diagram which shows the image which took the difference of the image shown in FIG. 9, and the image shown in FIG.
- FIG. 12 is a schematic diagram illustrating an example in which the image shown in FIG. 11 is subjected to GSTH processing in a region long in the y direction. It is a flowchart which shows the flow of the hanger detection in Example 2 of this invention.
- the process denoted as GSTH process indicates that the expansion process illustrated in FIG. 5 is performed after the contraction process illustrated in FIG. 4, and the process denoted as gsth process is a process obtained by simplifying the GSTH process. It is assumed that only the contraction process shown in FIG. 4 is performed without performing the expansion process shown.
- the hanger detection apparatus using image processing in this embodiment includes a line sensor camera 2 installed on the roof of a train vehicle 1 and an image processing unit 3 installed inside the vehicle 1. ing.
- the trolley wire 4 is supported by a plurality of hangers 6 that are installed on the platform wire 5 at approximately equal intervals.
- the line sensor camera 2 is installed on the side of the roof of the vehicle 1, the installation angle and the elevation angle so that the optical axis thereof is orthogonal to the traveling direction of the vehicle 1 and one hanger 6 is contained in the field of view. Is set.
- an alternate long and short dash line in FIG. 1 indicates a photographing line.
- An image I (hereinafter referred to as a line sensor image) I as shown in FIG. 8 acquired by the line sensor camera 2 is input to the image processing unit 3.
- the trolley line 4, the overhead line 5, and the four hangers 6 are displayed in the line sensor image I.
- the image processing unit 3 analyzes the line sensor image I and detects the hanger 6, and includes an arithmetic device 31 and a recording device 32.
- the arithmetic unit 31 includes a GSTH processing unit 31a, a hanger detection unit 31b, and a memory 31c.
- the GSTH processing unit 31a performs image luminance inversion processing on the line sensor image I based on the parameters input from the recording device 32 via the memory 31c and the line sensor image I input from the line sensor camera 2 via the memory 31c. And GSTH treatment.
- the image luminance inversion processing is processing for inverting the luminance value for each line in the x direction with respect to the line sensor image I. However, if the luminance value of the main component in the x direction is dark, it is determined that the night or a tunnel, and luminance inversion processing is not performed.
- the GSTH process is a gray scale-top hat process (Gray Scale-Top Hat process). As the name implies, the top hat process is applied to a gray scale image.
- the Top Hat process is a process of subtracting an opening image (an image subjected to a contraction process and an expansion process for the same number of times) from the original image.
- GSTH processing by the GSTH processing unit 31a will be briefly described with reference to FIGS.
- GSTH processing is performed according to the following flow.
- a range of N pixels three pixels in FIG. 3
- Shrinkage processing is performed by writing the luminance value of the darkest pixel to another buffer (shrinkage processing buffer) 12-m while shifting to create a shrinkage processed image 12 (12-M).
- GSTH image (transformed image) I D as shown in FIG. 12 GSTH processing has been performed is input through the memory 31c to the hanger detection unit 31b.
- the hanger detection unit 31b detects the hanger 6 by binarization processing or the like based on the parameters input from the recording device 32 via the memory 31c and the converted image input from the GSTH processing unit 31a via the memory 31c.
- the installed hangers 6 are installed at predetermined equal intervals (distances)
- the position in the image can be grasped by counting the number of detected hangers 6.
- only the hanger 6 installed vertically is detected in this embodiment, and the inclined hanger 6 is not detected.
- the number of hangers 6 between the utility poles is managed in advance as equipment data. Therefore, by separately interlocking with the utility pole detection signal, when the number of hangers 6 for each utility pole is small, it can be detected as the hangers 6 having an abnormal angle.
- Information on the hanger 6 detected by the hanger detection unit 31b is output to the memory 31c as a hanger detection result.
- the memory 31c temporarily stores various data. Various data are stored in the recording device 32. Note that the parameters described above are the number of pixels N for setting the search range, the number of pixels w and h required when performing GSTH processing, the binarization threshold value, and the like.
- a line sensor image I as shown in FIG. 8 is first input from the line sensor camera 2 (step S1).
- the x direction shown in FIG. 8 corresponds to the photographing line of the line sensor camera 2 in FIG.
- the y direction shown in FIG. 8 is the time taken by the line sensor camera 2 line by line.
- An image taken from the vehicle 1 traveling at a constant speed is as shown in FIG.
- the GSTH processing unit 31a performs a process of inverting the luminance value for the line sensor image I (step S2).
- the luminance inversion is processed for each line in the x direction of the line sensor image I, and when the luminance value of the main component in the x direction is dark, it is determined as nighttime or tunnel and the luminance is not inverted.
- the tunnel portion shown in the upper part of FIG. 8 whose background is a dark color can be assimilated with a section whose background such as the sky is a light color.
- Step S3 the contraction process shown in FIG. 4 for acquiring the darkest pixel in the region of w ⁇ 1 [pixel] long in the x direction is performed, and the expansion process shown in FIG. 5 for acquiring the brightest pixel is performed.
- a first GSTH image I B of white points as shown in FIG. 10 are extracted for the following width w x direction.
- w corresponds to the width of the strip such as the trolley wire 4 and is calculated experimentally.
- the first GSTH image I B is hangers 6 and telephone poles and structures such as buildings against inverted luminance image I A (hereinafter, a disturbance hereinafter) has a picture 7 is removed .
- the GSTH processing unit 31a similarly subtracts the first GSTH image I B from the luminance inverted image I A to obtain a difference image I C as shown in FIG. 11 (step S4).
- the difference image I C is an image in which the hanger 6 and the disturbance 7 such as a utility pole or a building are extracted.
- region which becomes negative by a difference process is made, 0 or less shall be rounded up to 0.
- the difference image I C is GSTH processed in the y direction in the GSTH processing unit 31a (step S5). That is, the contraction process shown in FIG. 4 for acquiring the darkest pixel in the 1 ⁇ h [pixel] region long in the y direction is performed, and then the expansion process shown in FIG. 5 for acquiring the brightest pixel is performed.
- an image (hereinafter referred to as a second GSTH image) ID in which the white portion is extracted in the y direction and with a length of h or less is obtained.
- h corresponds to the diameter of the hanger 6 and is calculated experimentally.
- the second GSTH image I D is an image in which only the hangers 6 are extracted to the difference image I C.
- the second GSTH image ID is input as a converted image to the hanger detector 31b via the memory 31c.
- step S6 the hanger detection unit 31b, the second GSTH image I D shown in FIG. 12, for detecting the hanger 6 using binarization process or the like. Since the installed hangers 6 are installed at predetermined equal intervals (distances), the number of detected hangers 6 is counted to grasp the position in the image.
- Step P1 to Step P6 The above processing from Step P1 to Step P6 is performed until the input of all the line sensor images I is completed.
- the GSTH processing is a combination of the shrinkage processing shown in FIG. 4 and the expansion processing shown in FIG.
- the hanger detection apparatus using image processing according to the present embodiment has the following advantages that make use of the features of GSTH. -Only the hanger 6 reflected in a predetermined direction and a predetermined thickness can be detected.
- the hanger 6 can be detected by eliminating the disturbance 7 having characteristics different from those of the hanger 6 such as the tunnel wellhead and the utility pole 7.
- the abnormal hanger 6 can also be detected by comparing the number of hangers 6 detected in the present embodiment with the number of normal hangers 6 for each utility pole that is managed in advance as facility data.
- the hanger detection apparatus using image processing according to the present embodiment is different from the first embodiment in that the processing in the GSTH processing unit 31a is simplified.
- the apparatus configuration is the same as that of the hanger detection apparatus based on image processing according to the first embodiment, and the description thereof will be omitted below, focusing on the processing in the image processing unit 3.
- a line sensor image I as shown in FIG. 8 is first input from the line sensor camera 2 (step S11), and then In the GSTH processing unit 31a, the line sensor image I is subjected to a process of inverting the luminance value for a photographing line whose main component luminance value is light in the x direction (step S12). This gives inverted luminance image I A, as shown in FIG.
- step S13 gsth processing the luminance reversed image I A shown in FIG. 8 the x-direction. That is, the contraction process shown in FIG. 4 for acquiring the darkest pixel in the region of w ⁇ 1 [pixel] long in the x direction is performed, while the expansion process shown in FIG. 5 for acquiring the brightest pixel is not performed. As a result, a gsth image I C in which white portions as shown in FIG. 11 are extracted with a width w or less in the x direction is obtained. Note that w corresponds to the width of the strip such as the trolley wire 4 and is calculated experimentally.
- the GSTH processing unit 31a similarly performs GSTH processing on the gsth image I C in the y direction (step S14). That is, the contraction process shown in FIG. 4 for acquiring the darkest pixel in the 1 ⁇ h [pixel] region long in the y direction is performed, and then the expansion process shown in FIG. 5 for acquiring the brightest pixel is performed. As a result, as shown in FIG. 12, a GSTH image ID in which white portions are extracted in the y direction and with a length equal to or shorter than h is obtained. Note that h corresponds to the diameter of the hanger 6 and is calculated experimentally.
- the GSTH image ID is input as a converted image to the hanger detector 31b via the memory 31c.
- the hanger detection unit 31b detects the hanger 6 from the GSTH image ID shown in FIG. 12 using binarization processing or the like (step S15). Since the hangers 6 are installed at a predetermined interval (distance), the current position of the vehicle 1 is grasped by counting the detected hangers 6, and the installation angle of the hangers 6 has a management value. Inspect whether the installation angle is.
- Step P11 to Step P15 The above processing of Step P11 to Step P15 is performed until the input of all the line sensor images I is completed.
- the luminance inversion image I A is subjected to gsth processing in the x direction (only the contraction processing shown in FIG. 4 is performed), thereby simplifying the processing. Therefore, there is an advantage that the hanger detection processing can be speeded up as compared with the first embodiment.
- the hanger 6 detected on the image is shortened by performing the gsth process, the present embodiment is intended to determine whether or not the hanger 6 is present. Absent.
- the present invention is suitable for application to a hanger detection apparatus using image processing.
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Abstract
This device for hanger detection by image processing detects hangers (6) in an image, and is equipped with: a line sensor camera (2) that captures an image of hangers (6) from the roof of a vehicle (1), the hangers (6) being installed with equal spacing and support a trolley line (4); and an image processing unit (3) that is installed within the vehicle (1) and analyzes the image obtained by the line sensor camera (2). The device for hanger detection is configured such that the image processing unit (3) is provided with: a gray scale-top hat processing unit (31a) which sequentially subjects each line sensor image input from the line sensor camera (2) to the gray scale-top hat processing in the imaging line direction and time direction of the line sensor camera (2) and acquires a gray scale-top hat image where the hangers (6) in the image are highlighted; and a hanger detection unit (31b) which detects the hangers (6) from the gray scale-top hat image.
Description
本発明は、ハンガーを画像処理によって検出し、電車車両の走行位置やハンガーの角度異常を検出する画像処理によるハンガー検出装置に関する。
The present invention relates to a hanger detection device by image processing that detects a hanger by image processing and detects a travel position of a train car and an angle abnormality of the hanger.
まずハンガーを検出する必要性について説明する。
鉄道事業者では、走行中に電車線路を録画し、録画画像から電車の走行位置を特定している。従来、電車の走行位置を特定する技術としてはGPSやATC技術があるが、これらは電車の運行上支障がない程度の精度を有するものの、画像中から電車の走行位置を特定するような場合には、より正確に走行位置を把握することが要求されている。 First, the necessity of detecting hangers will be described.
A railway operator records a train track while traveling and specifies the traveling position of the train from the recorded image. Conventionally, there are GPS and ATC technologies for identifying the location of trains. However, these technologies are accurate enough not to interfere with train operation, but when train locations are identified from images. Therefore, it is required to grasp the traveling position more accurately.
鉄道事業者では、走行中に電車線路を録画し、録画画像から電車の走行位置を特定している。従来、電車の走行位置を特定する技術としてはGPSやATC技術があるが、これらは電車の運行上支障がない程度の精度を有するものの、画像中から電車の走行位置を特定するような場合には、より正確に走行位置を把握することが要求されている。 First, the necessity of detecting hangers will be described.
A railway operator records a train track while traveling and specifies the traveling position of the train from the recorded image. Conventionally, there are GPS and ATC technologies for identifying the location of trains. However, these technologies are accurate enough not to interfere with train operation, but when train locations are identified from images. Therefore, it is required to grasp the traveling position more accurately.
また、正常なハンガーは鉛直に架設されているが、温度変化等により鉛直方向に対して傾斜を有すると電車の集電特性を劣化させるため、ハンガーの角度を把握することも重要となっている。従来、ハンガーを検出する技術として、下記特許文献1、2が公知となっている。特許文献1は、撮影した画像からテンプレートマッチング処理または鉛直のエッジ検出処理によって、ハンガーを検出する特許である。また特許文献2は、撮影した画像から、Hough変換処理または輝度ヒストグラム処理または2本の直線の交点を検出して、ハンガーを検出する特許である。
In addition, normal hangers are installed vertically, but it is important to know the angle of the hangers because the current collection characteristics of the train deteriorate if they are inclined with respect to the vertical direction due to temperature changes. . Conventionally, Patent Documents 1 and 2 are known as techniques for detecting hangers. Patent Document 1 is a patent that detects hangers from captured images by template matching processing or vertical edge detection processing. Patent Document 2 is a patent for detecting a hanger by detecting an intersection of two straight lines from a captured image by detecting a Hough transform process, a luminance histogram process, or two straight lines.
上記特許文献1、2に開示された発明は、単純な線条構成であればハンガー検出が可能であるが、わたり線や、オーバーラップ箇所など、図8に示すように複数の線条4,5が交差する箇所では、ハンガー6を検出することが難しい。
特許文献1は鉛直のエッジ検出によってハンガーを検出する。一般的なエッジ検出は2pixel間の微分値の大きい箇所をエッジとして検出する。2pixelの局所的な検出は、誤検出が多い課題がある。
特許文献2は、Hough変換でハンガーを検出する特許である。Hough変換は画像全体の特徴とハンガー特徴との相対的な投票量を用いてハンガーを見つけるので、図8のように画像全体に対して小さく写るハンガー6を検出することは難しい。 The inventions disclosed in Patent Documents 1 and 2 are capable of detecting hangers as long as they have a simple line configuration. However, as shown in FIG. It is difficult to detect the hanger 6 at a location where 5 intersects.
Patent document 1 detects a hanger by vertical edge detection. In general edge detection, a portion having a large differential value between 2 pixels is detected as an edge. The local detection of 2 pixels has a problem with many false detections.
Patent document 2 is a patent which detects a hanger by Hough transformation. The Hough transform finds a hanger using a relative vote amount between the feature of the entire image and the hanger feature, so it is difficult to detect the hanger 6 that appears small relative to the entire image as shown in FIG.
特許文献1は鉛直のエッジ検出によってハンガーを検出する。一般的なエッジ検出は2pixel間の微分値の大きい箇所をエッジとして検出する。2pixelの局所的な検出は、誤検出が多い課題がある。
特許文献2は、Hough変換でハンガーを検出する特許である。Hough変換は画像全体の特徴とハンガー特徴との相対的な投票量を用いてハンガーを見つけるので、図8のように画像全体に対して小さく写るハンガー6を検出することは難しい。 The inventions disclosed in
関連特許として、上記特許文献3がある。これはトロリ線の摩耗を測定する発明で、GSTH処理(図4,5参照)で背景除去を行いトロリ線の摩耗した箇所をロバストに検出する特許である。特許文献3のGSTH処理は、トロリ線の下面の照明光が白く反射することを利用する点に特徴がある。本件の目的とするハンガーには白く反射する箇所は無いので、特許文献3を使用してハンガー検出させることは難しい。
There is Patent Document 3 as a related patent. This is an invention for measuring wear of a trolley wire, and is a patent for robustly detecting a worn portion of a trolley wire by removing the background by GSTH processing (see FIGS. 4 and 5). The GSTH process of Patent Document 3 is characterized in that the illumination light on the lower surface of the trolley wire is reflected in white. Since there is no part which reflects white in the hanger which is the object of this case, it is difficult to detect the hanger using Patent Document 3.
このようなことから本発明は、より高精度にハンガーを検出することを可能とした画像処理によるハンガー検出装置を提供することを目的とする。
Therefore, an object of the present invention is to provide a hanger detection device using image processing that can detect a hanger with higher accuracy.
上記の課題を解決するための第1の発明に係る画像処理によるハンガー検出装置は、
等間隔に設置されトロリ線を支持するハンガーを車両の屋根上から撮影するラインセンサカメラと、前記車両の内部に設置され前記ラインセンサカメラによって得られる画像を解析する画像処理部とを備えて前記画像中のハンガーを検出する画像処理によるハンガー検出装置であって、
前記画像処理部が、
前記ラインセンサカメラから入力されるラインセンサ画像に対して前記ラインセンサカメラの撮影ライン方向及び時間方向に順次GSTH処理を行って前記画像中の前記ハンガーを強調したGSTH画像を取得するGSTH処理部と、
前記GSTH画像からハンガーを検出するハンガー検出部と
を有することを特徴とする。 A hanger detection device by image processing according to the first invention for solving the above-mentioned problems is
A line sensor camera for photographing a hanger that is installed at equal intervals and supports a trolley line from the roof of the vehicle, and an image processing unit that is installed inside the vehicle and analyzes an image obtained by the line sensor camera, A hanger detection device by image processing for detecting a hanger in an image,
The image processing unit
A GSTH processing unit that sequentially performs GSTH processing on a line sensor image input from the line sensor camera in a shooting line direction and a time direction of the line sensor camera to obtain a GSTH image in which the hanger in the image is emphasized; ,
And a hanger detector for detecting a hanger from the GSTH image.
等間隔に設置されトロリ線を支持するハンガーを車両の屋根上から撮影するラインセンサカメラと、前記車両の内部に設置され前記ラインセンサカメラによって得られる画像を解析する画像処理部とを備えて前記画像中のハンガーを検出する画像処理によるハンガー検出装置であって、
前記画像処理部が、
前記ラインセンサカメラから入力されるラインセンサ画像に対して前記ラインセンサカメラの撮影ライン方向及び時間方向に順次GSTH処理を行って前記画像中の前記ハンガーを強調したGSTH画像を取得するGSTH処理部と、
前記GSTH画像からハンガーを検出するハンガー検出部と
を有することを特徴とする。 A hanger detection device by image processing according to the first invention for solving the above-mentioned problems is
A line sensor camera for photographing a hanger that is installed at equal intervals and supports a trolley line from the roof of the vehicle, and an image processing unit that is installed inside the vehicle and analyzes an image obtained by the line sensor camera, A hanger detection device by image processing for detecting a hanger in an image,
The image processing unit
A GSTH processing unit that sequentially performs GSTH processing on a line sensor image input from the line sensor camera in a shooting line direction and a time direction of the line sensor camera to obtain a GSTH image in which the hanger in the image is emphasized; ,
And a hanger detector for detecting a hanger from the GSTH image.
また、第2の発明に係る画像処理によるハンガー検出装置は、第1の発明において、
前記GSTH処理部が、前記GSTH処理として、前記ラインセンサ画像に対し、前記ラインセンサカメラの撮影ライン方向について収縮処理を行った後膨張処理を行って第一のGSTH画像を取得し、前記ラインセンサ画像と前記第一のGSTH画像との差分を取って差分画像を取得し、前記差分画像に対し時間方向について収縮処理を行った後膨張処理を行って前記ラインセンサ画像中の前記ハンガーを強調した第二のGSTH画像を取得し、
前記ハンガー検出部が、前記第二のGSTH画像から前記ハンガーを検出する
ことを特徴とする。 Moreover, the hanger detection apparatus by the image processing which concerns on 2nd invention in 1st invention,
The GSTH processing unit obtains a first GSTH image by performing an expansion process on the line sensor image after performing a contraction process on the imaging line direction of the line sensor camera as the GSTH process, and acquiring the first GSTH image. A difference image is obtained by taking a difference between the image and the first GSTH image, and after the shrinkage process is performed on the difference image in the time direction, the expansion process is performed to emphasize the hanger in the line sensor image Get a second GSTH image,
The hanger detection unit detects the hanger from the second GSTH image.
前記GSTH処理部が、前記GSTH処理として、前記ラインセンサ画像に対し、前記ラインセンサカメラの撮影ライン方向について収縮処理を行った後膨張処理を行って第一のGSTH画像を取得し、前記ラインセンサ画像と前記第一のGSTH画像との差分を取って差分画像を取得し、前記差分画像に対し時間方向について収縮処理を行った後膨張処理を行って前記ラインセンサ画像中の前記ハンガーを強調した第二のGSTH画像を取得し、
前記ハンガー検出部が、前記第二のGSTH画像から前記ハンガーを検出する
ことを特徴とする。 Moreover, the hanger detection apparatus by the image processing which concerns on 2nd invention in 1st invention,
The GSTH processing unit obtains a first GSTH image by performing an expansion process on the line sensor image after performing a contraction process on the imaging line direction of the line sensor camera as the GSTH process, and acquiring the first GSTH image. A difference image is obtained by taking a difference between the image and the first GSTH image, and after the shrinkage process is performed on the difference image in the time direction, the expansion process is performed to emphasize the hanger in the line sensor image Get a second GSTH image,
The hanger detection unit detects the hanger from the second GSTH image.
また、第3の発明に係る画像処理によるハンガー検出装置は、第1の発明において、
前記GSTH処理部が、前記GSTH処理として、前記ラインセンサ画像に対し、前記ラインセンサカメラの撮影ライン方向については収縮処理のみを行ってgsth画像を取得し、前記gsth画像に対し時間方向について収縮処理を行った後膨張処理を行って前記ラインセンサ画像中の前記ハンガーを強調した前記GSTH画像を取得し、
前記ハンガー検出部が、前記GSTH画像から前記ハンガーを検出する
ことを特徴とする。 Moreover, the hanger detection apparatus by the image processing which concerns on 3rd invention in 1st invention,
As the GSTH processing, the GSTH processing unit obtains a gsth image by performing only a contraction process on the line sensor image in the photographing line direction of the line sensor camera, and acquires a gsth image in the time direction on the gsth image. The GSTH image in which the hanger in the line sensor image is emphasized by performing an expansion process after performing
The hanger detection unit detects the hanger from the GSTH image.
前記GSTH処理部が、前記GSTH処理として、前記ラインセンサ画像に対し、前記ラインセンサカメラの撮影ライン方向については収縮処理のみを行ってgsth画像を取得し、前記gsth画像に対し時間方向について収縮処理を行った後膨張処理を行って前記ラインセンサ画像中の前記ハンガーを強調した前記GSTH画像を取得し、
前記ハンガー検出部が、前記GSTH画像から前記ハンガーを検出する
ことを特徴とする。 Moreover, the hanger detection apparatus by the image processing which concerns on 3rd invention in 1st invention,
As the GSTH processing, the GSTH processing unit obtains a gsth image by performing only a contraction process on the line sensor image in the photographing line direction of the line sensor camera, and acquires a gsth image in the time direction on the gsth image. The GSTH image in which the hanger in the line sensor image is emphasized by performing an expansion process after performing
The hanger detection unit detects the hanger from the GSTH image.
また、第4の発明に係る画像処理によるハンガー検出装置は、第1から第3のいずれか一つの発明において、
前記GSTH処理部が、前記ラインセンサ画像に対し、前記ラインセンサカメラの撮影ライン方向について1ラインずつ、当該撮影ライン方向で主成分の輝度値が淡色の場合は輝度値を反転し主成分の輝度値が濃色の場合は輝度値を反転しない輝度反転処理を行った後、前記GSTH処理を行う
ことを特徴とする。 Moreover, the hanger detection apparatus by the image processing which concerns on 4th invention is the invention in any one of 1st to 3rd.
The GSTH processing unit inverts the luminance value for the line sensor image, one line at a time for the shooting line direction of the line sensor camera, and the luminance value of the main component in the shooting line direction when the luminance value of the main component is light color. When the value is a dark color, the GSTH process is performed after the luminance inversion process that does not invert the luminance value.
前記GSTH処理部が、前記ラインセンサ画像に対し、前記ラインセンサカメラの撮影ライン方向について1ラインずつ、当該撮影ライン方向で主成分の輝度値が淡色の場合は輝度値を反転し主成分の輝度値が濃色の場合は輝度値を反転しない輝度反転処理を行った後、前記GSTH処理を行う
ことを特徴とする。 Moreover, the hanger detection apparatus by the image processing which concerns on 4th invention is the invention in any one of 1st to 3rd.
The GSTH processing unit inverts the luminance value for the line sensor image, one line at a time for the shooting line direction of the line sensor camera, and the luminance value of the main component in the shooting line direction when the luminance value of the main component is light color. When the value is a dark color, the GSTH process is performed after the luminance inversion process that does not invert the luminance value.
本発明によれば、画像中に所定の方向で且つ所定の太さより細い直線として存在するハンガーのみを抽出することができるため、設置角度が管理値内にある正常なハンガーのみを高精度に検出することができる。
According to the present invention, it is possible to extract only hangers that exist in the image in a predetermined direction and as a straight line that is thinner than a predetermined thickness, so that only normal hangers whose installation angle is within the control value can be detected with high accuracy. can do.
以下、図面を参照しつつ本発明に係る画像処理によるハンガー検出装置について説明するが、本発明は以下の実施例に限定されるものではない。
以下の説明において、GSTH処理と表記する処理は図4に示す収縮処理後図5に示す膨張処理を行うものを示し、gsth処理と表記する処理はGSTH処理を簡略化した処理で、図5に示す膨張処理を行わず、図4に示す収縮処理だけを行うものを示すものとする。 Hereinafter, a hanger detection apparatus using image processing according to the present invention will be described with reference to the drawings, but the present invention is not limited to the following embodiments.
In the following description, the process denoted as GSTH process indicates that the expansion process illustrated in FIG. 5 is performed after the contraction process illustrated in FIG. 4, and the process denoted as gsth process is a process obtained by simplifying the GSTH process. It is assumed that only the contraction process shown in FIG. 4 is performed without performing the expansion process shown.
以下の説明において、GSTH処理と表記する処理は図4に示す収縮処理後図5に示す膨張処理を行うものを示し、gsth処理と表記する処理はGSTH処理を簡略化した処理で、図5に示す膨張処理を行わず、図4に示す収縮処理だけを行うものを示すものとする。 Hereinafter, a hanger detection apparatus using image processing according to the present invention will be described with reference to the drawings, but the present invention is not limited to the following embodiments.
In the following description, the process denoted as GSTH process indicates that the expansion process illustrated in FIG. 5 is performed after the contraction process illustrated in FIG. 4, and the process denoted as gsth process is a process obtained by simplifying the GSTH process. It is assumed that only the contraction process shown in FIG. 4 is performed without performing the expansion process shown.
〔GSTH処理を用いたハンガー検出装置:GSTH(A-GSTH(A))〕
図1から図12を用いて本発明の実施例1に係る画像処理によるハンガー検出装置の詳細を説明する。 [Hanger detector using GSTH treatment: GSTH (A-GSTH (A))]
Details of the hanger detection apparatus using image processing according to the first embodiment of the present invention will be described with reference to FIGS.
図1から図12を用いて本発明の実施例1に係る画像処理によるハンガー検出装置の詳細を説明する。 [Hanger detector using GSTH treatment: GSTH (A-GSTH (A))]
Details of the hanger detection apparatus using image processing according to the first embodiment of the present invention will be described with reference to FIGS.
図1に示すように、本実施例において画像処理によるハンガー検出装置は、電車車両1の屋根上に設置されたラインセンサカメラ2と、車両1の内部に設置された画像処理部3とを備えている。
また、トロリ線4はちょう架線5に概ね等間隔に設置された複数のハンガー6によって支持されている。 As shown in FIG. 1, the hanger detection apparatus using image processing in this embodiment includes aline sensor camera 2 installed on the roof of a train vehicle 1 and an image processing unit 3 installed inside the vehicle 1. ing.
Thetrolley wire 4 is supported by a plurality of hangers 6 that are installed on the platform wire 5 at approximately equal intervals.
また、トロリ線4はちょう架線5に概ね等間隔に設置された複数のハンガー6によって支持されている。 As shown in FIG. 1, the hanger detection apparatus using image processing in this embodiment includes a
The
ラインセンサカメラ2は、車両1の屋根上の側方に設置され、その光軸が車両1の進行方向に直交するように、且つ、その視野に一つのハンガー6が収まるように設置角度及び仰角を設定されている。ここで、図1中の一点鎖線は撮影ラインを示している。ラインセンサカメラ2によって取得した図8に示すような画像(以下、ラインセンサ画像という)Iは画像処理部3に入力される。
なお、図8に示す例においてラインセンサ画像Iには、トロリ線4、ちょう架線5、及び四つのハンガー6が表示されている。 Theline sensor camera 2 is installed on the side of the roof of the vehicle 1, the installation angle and the elevation angle so that the optical axis thereof is orthogonal to the traveling direction of the vehicle 1 and one hanger 6 is contained in the field of view. Is set. Here, an alternate long and short dash line in FIG. 1 indicates a photographing line. An image I (hereinafter referred to as a line sensor image) I as shown in FIG. 8 acquired by the line sensor camera 2 is input to the image processing unit 3.
In the example shown in FIG. 8, thetrolley line 4, the overhead line 5, and the four hangers 6 are displayed in the line sensor image I.
なお、図8に示す例においてラインセンサ画像Iには、トロリ線4、ちょう架線5、及び四つのハンガー6が表示されている。 The
In the example shown in FIG. 8, the
画像処理部3はラインセンサ画像Iを解析してハンガー6を検出するものであり、演算装置31と記録装置32とから構成されている。
The image processing unit 3 analyzes the line sensor image I and detects the hanger 6, and includes an arithmetic device 31 and a recording device 32.
図2に示すように、演算装置31はGSTH処理部31a、ハンガー検出部31b、及びメモリ31cを備えている。
As shown in FIG. 2, the arithmetic unit 31 includes a GSTH processing unit 31a, a hanger detection unit 31b, and a memory 31c.
GSTH処理部31aは、記録装置32からメモリ31cを経て入力されるパラメータとラインセンサカメラ2からメモリ31cを経て入力されたラインセンサ画像Iとに基づき、ラインセンサ画像Iに対して画像輝度反転処理及びGSTH処理を行う。
ここで、画像輝度反転処理とはラインセンサ画像Iに対してx方向の1ラインずつ輝度値を反転する処理である。ただし、x方向で主成分の輝度値が濃色の場合は、夜間やトンネルと判定し輝度反転処理は行わないものとする。
また、GSTH処理とはグレイスケール-トップハット処理(Gray Scale-Top Hat処理)であり、その名の通り、グレイスケール画像に対してTop Hat処理をかけるものである。Top Hat処理とは原画像に対してオープニング画像(同じ回数分収縮→膨張処理した画像)を差し引く処理のことである。 TheGSTH processing unit 31a performs image luminance inversion processing on the line sensor image I based on the parameters input from the recording device 32 via the memory 31c and the line sensor image I input from the line sensor camera 2 via the memory 31c. And GSTH treatment.
Here, the image luminance inversion processing is processing for inverting the luminance value for each line in the x direction with respect to the line sensor image I. However, if the luminance value of the main component in the x direction is dark, it is determined that the night or a tunnel, and luminance inversion processing is not performed.
The GSTH process is a gray scale-top hat process (Gray Scale-Top Hat process). As the name implies, the top hat process is applied to a gray scale image. The Top Hat process is a process of subtracting an opening image (an image subjected to a contraction process and an expansion process for the same number of times) from the original image.
ここで、画像輝度反転処理とはラインセンサ画像Iに対してx方向の1ラインずつ輝度値を反転する処理である。ただし、x方向で主成分の輝度値が濃色の場合は、夜間やトンネルと判定し輝度反転処理は行わないものとする。
また、GSTH処理とはグレイスケール-トップハット処理(Gray Scale-Top Hat処理)であり、その名の通り、グレイスケール画像に対してTop Hat処理をかけるものである。Top Hat処理とは原画像に対してオープニング画像(同じ回数分収縮→膨張処理した画像)を差し引く処理のことである。 The
Here, the image luminance inversion processing is processing for inverting the luminance value for each line in the x direction with respect to the line sensor image I. However, if the luminance value of the main component in the x direction is dark, it is determined that the night or a tunnel, and luminance inversion processing is not performed.
The GSTH process is a gray scale-top hat process (Gray Scale-Top Hat process). As the name implies, the top hat process is applied to a gray scale image. The Top Hat process is a process of subtracting an opening image (an image subjected to a contraction process and an expansion process for the same number of times) from the original image.
以下に、図3から図6を用いてGSTH処理部31aによるGSTH処理について簡単に説明する。GSTH処理は、以下の流れで行う。
(1)図4に示すように、図3に示す原画像11に対してN画素(図3では三画素)の範囲(以下、探索範囲という)SD-m(m=1~M)をずらしながらそれぞれ最も暗い画素の輝度値を別バッファ(収縮処理バッファ)12-mに書き込む収縮処理を行い、収縮処理画像12(12-M)を作成する。
(2)続いて、図5に示すように、収縮処理画像12に対してN画素(本実施例では三画素)の範囲(以下、探索範囲)SL-mをずらしながらそれぞれ最も明るい画素の輝度値を別バッファ(膨張処理バッファ)13-mに書き込む膨張処理を行い、オープニング画像13(13-M)を作成する。
(3)続いて、原画像11から(2)で作成したオープニング画像13(13-M)を差し引く。
以上の処理を行うことで、図6に示すように画像内の暗い部分に囲まれた明るい画素を強調したGSTH画像14が得られる。 Hereinafter, GSTH processing by theGSTH processing unit 31a will be briefly described with reference to FIGS. GSTH processing is performed according to the following flow.
(1) As shown in FIG. 4, a range of N pixels (three pixels in FIG. 3) S D −m (m = 1 to M) is applied to theoriginal image 11 shown in FIG. Shrinkage processing is performed by writing the luminance value of the darkest pixel to another buffer (shrinkage processing buffer) 12-m while shifting to create a shrinkage processed image 12 (12-M).
(2) Subsequently, as shown in FIG. 5, while shifting the range (hereinafter referred to as the search range) S L -m of N pixels (three pixels in this embodiment) with respect to the contraction processedimage 12, An expansion process for writing the luminance value into another buffer (expansion process buffer) 13-m is performed to create an opening image 13 (13-M).
(3) Subsequently, the opening image 13 (13-M) created in (2) is subtracted from theoriginal image 11.
By performing the above processing, aGSTH image 14 in which bright pixels surrounded by a dark portion in the image are emphasized as shown in FIG. 6 is obtained.
(1)図4に示すように、図3に示す原画像11に対してN画素(図3では三画素)の範囲(以下、探索範囲という)SD-m(m=1~M)をずらしながらそれぞれ最も暗い画素の輝度値を別バッファ(収縮処理バッファ)12-mに書き込む収縮処理を行い、収縮処理画像12(12-M)を作成する。
(2)続いて、図5に示すように、収縮処理画像12に対してN画素(本実施例では三画素)の範囲(以下、探索範囲)SL-mをずらしながらそれぞれ最も明るい画素の輝度値を別バッファ(膨張処理バッファ)13-mに書き込む膨張処理を行い、オープニング画像13(13-M)を作成する。
(3)続いて、原画像11から(2)で作成したオープニング画像13(13-M)を差し引く。
以上の処理を行うことで、図6に示すように画像内の暗い部分に囲まれた明るい画素を強調したGSTH画像14が得られる。 Hereinafter, GSTH processing by the
(1) As shown in FIG. 4, a range of N pixels (three pixels in FIG. 3) S D −m (m = 1 to M) is applied to the
(2) Subsequently, as shown in FIG. 5, while shifting the range (hereinafter referred to as the search range) S L -m of N pixels (three pixels in this embodiment) with respect to the contraction processed
(3) Subsequently, the opening image 13 (13-M) created in (2) is subtracted from the
By performing the above processing, a
GSTH処理部31aにおいて画像輝度反転処理後、GSTH処理が施された図12に示すようなGSTH画像(変換画像)IDはメモリ31cを経てハンガー検出部31bへ入力される。
After the image brightness inversion operation in GSTH processing unit 31a, GSTH image (transformed image) I D as shown in FIG. 12 GSTH processing has been performed is input through the memory 31c to the hanger detection unit 31b.
ハンガー検出部31bは、記録装置32からメモリ31cを経て入力されるパラメータとGSTH処理部31aからメモリ31cを経て入力される変換画像とに基づいて、二値化処理等によりハンガー6を検出する。
ここで、架設されているハンガー6は所定の等間隔(距離)で設置されているので、検出したハンガー6の数を計数することにより画像中の位置を把握することができる。
また、図12に示すように、本実施例では鉛直に設置されたハンガー6のみを検出し、傾斜したハンガー6は検出されない。また電柱間のハンガー6の数は、予め設備データとして管理されている。したがって別途電柱検出信号と連動させることで、電柱ごとのハンガー6の本数が少ない場合は、異常角度のハンガー6として検出できる。
ハンガー検出部31bによって検出したハンガー6の情報は、ハンガー検出結果としてメモリ31cへ出力される。 Thehanger detection unit 31b detects the hanger 6 by binarization processing or the like based on the parameters input from the recording device 32 via the memory 31c and the converted image input from the GSTH processing unit 31a via the memory 31c.
Here, since the installedhangers 6 are installed at predetermined equal intervals (distances), the position in the image can be grasped by counting the number of detected hangers 6.
Moreover, as shown in FIG. 12, only thehanger 6 installed vertically is detected in this embodiment, and the inclined hanger 6 is not detected. The number of hangers 6 between the utility poles is managed in advance as equipment data. Therefore, by separately interlocking with the utility pole detection signal, when the number of hangers 6 for each utility pole is small, it can be detected as the hangers 6 having an abnormal angle.
Information on thehanger 6 detected by the hanger detection unit 31b is output to the memory 31c as a hanger detection result.
ここで、架設されているハンガー6は所定の等間隔(距離)で設置されているので、検出したハンガー6の数を計数することにより画像中の位置を把握することができる。
また、図12に示すように、本実施例では鉛直に設置されたハンガー6のみを検出し、傾斜したハンガー6は検出されない。また電柱間のハンガー6の数は、予め設備データとして管理されている。したがって別途電柱検出信号と連動させることで、電柱ごとのハンガー6の本数が少ない場合は、異常角度のハンガー6として検出できる。
ハンガー検出部31bによって検出したハンガー6の情報は、ハンガー検出結果としてメモリ31cへ出力される。 The
Here, since the installed
Moreover, as shown in FIG. 12, only the
Information on the
メモリ31cは各種データを一時的に保管する。記録装置32には各種データが保存される。なお、上述したパラメータは、探索範囲を設定するための画素数N、GSTH処理を行う際に必要となるピクセル数w,hや、二値化しきい値等である。
The memory 31c temporarily stores various data. Various data are stored in the recording device 32. Note that the parameters described above are the number of pixels N for setting the search range, the number of pixels w and h required when performing GSTH processing, the binarization threshold value, and the like.
以下、図7に基づいて本実施例に係る画像処理によるハンガー検出装置における処理の流れを説明する。
Hereinafter, the flow of processing in the hanger detection apparatus using image processing according to the present embodiment will be described with reference to FIG.
図7に示すように、本実施例に係る画像処理によるハンガー検出装置においては、まずラインセンサカメラ2から図8に一例を示すようなラインセンサ画像Iを入力する(ステップS1)。なお、図8に示すx方向は、図1におけるラインセンサカメラ2の撮影ラインに対応する。また、図8に示すy方向は、ラインセンサカメラ2で1ラインずつ撮影した時間である。等速走行する車両1から撮影した画像は図8のようになる。
As shown in FIG. 7, in the hanger detection apparatus using image processing according to the present embodiment, a line sensor image I as shown in FIG. 8 is first input from the line sensor camera 2 (step S1). Note that the x direction shown in FIG. 8 corresponds to the photographing line of the line sensor camera 2 in FIG. Also, the y direction shown in FIG. 8 is the time taken by the line sensor camera 2 line by line. An image taken from the vehicle 1 traveling at a constant speed is as shown in FIG.
続いて、GSTH処理部31aにおいてラインセンサ画像Iに対して輝度値を反転する処理を行う(ステップS2)。これにより、図9に示すような輝度反転画像IAを得る。なお、上述したように輝度反転はラインセンサ画像Iのx方向の1ラインずつで処理し、x方向で主成分の輝度値が濃色の場合は、夜間やトンネルと判定し輝度反転しないため、図8の上部に示す背景が濃色であるトンネル箇所を、空等の背景が淡色である区間と同化させることができる。
Subsequently, the GSTH processing unit 31a performs a process of inverting the luminance value for the line sensor image I (step S2). This gives inverted luminance image I A, as shown in FIG. Note that, as described above, the luminance inversion is processed for each line in the x direction of the line sensor image I, and when the luminance value of the main component in the x direction is dark, it is determined as nighttime or tunnel and the luminance is not inverted. The tunnel portion shown in the upper part of FIG. 8 whose background is a dark color can be assimilated with a section whose background such as the sky is a light color.
続いて、同じくGSTH処理部31aにおいて、図8に示す輝度反転画像IAをx方向へGSTH処理する(ステップS3)。すなわち、x方向に長いw×1[pixel]の領域内で最も暗い画素を取得する図4に示す収縮処理を施し、次に最も明るい画素を取得する図5に示す膨張処理を施す。これによって図10に示すような白色箇所がx方向について幅w以下で抽出された第一のGSTH画像IBを得る。なおwはトロリ線4などの線条の幅に対応しており、実験的に算出する。図10に示す例では、第一のGSTH画像IBは、輝度反転画像IAに対してハンガー6及び電柱や建物等の構造物(以下、外乱という)7が除去された画像となっている。
Subsequently, likewise in GSTH processing unit 31a, to GSTH processing the luminance reversed image I A shown in FIG. 8 the x direction (Step S3). That is, the contraction process shown in FIG. 4 for acquiring the darkest pixel in the region of w × 1 [pixel] long in the x direction is performed, and the expansion process shown in FIG. 5 for acquiring the brightest pixel is performed. Thus obtaining a first GSTH image I B of white points as shown in FIG. 10 are extracted for the following width w x direction. Note that w corresponds to the width of the strip such as the trolley wire 4 and is calculated experimentally. In the example shown in FIG. 10, the first GSTH image I B is hangers 6 and telephone poles and structures such as buildings against inverted luminance image I A (hereinafter, a disturbance hereinafter) has a picture 7 is removed .
続いて、同じくGSTH処理部31aにおいて、輝度反転画像IAから第一のGSTH画像IBを差し引いて、図11に示すような差分画像ICを得る(ステップS4)。図11に示す例では、差分画像ICは、ハンガー6及び電柱や建物等の外乱7が抽出された画像となっている。なお差分処理で負になる領域ができる場合、0以下は0に切り上げるものとする。
Subsequently, the GSTH processing unit 31a similarly subtracts the first GSTH image I B from the luminance inverted image I A to obtain a difference image I C as shown in FIG. 11 (step S4). In the example illustrated in FIG. 11, the difference image I C is an image in which the hanger 6 and the disturbance 7 such as a utility pole or a building are extracted. In addition, when the area | region which becomes negative by a difference process is made, 0 or less shall be rounded up to 0.
続いて、同じくGSTH処理部31aにおいて、差分画像ICをy方向へGSTH処理する(ステップS5)。すなわち、y方向に長い1×h[pixel]の領域内で最も暗い画素を取得する図4に示す収縮処理を施し、次に最も明るい画素を取得する図5に示す膨張処理を施す。これによって図12に示すように白色箇所が、y方向でかつh以下の長さで抽出された画像(以下、第二のGSTH画像)IDを得る。なおhはハンガー6の直径に対応しており、実験的に算出する。図12に示す例では、第二のGSTH画像IDは、差分画像ICに対しハンガー6のみが抽出された画像となっている。
第二のGSTH画像IDは変換画像としてメモリ31cを経てハンガー検出部31bへ入力される。 Subsequently, the difference image I C is GSTH processed in the y direction in theGSTH processing unit 31a (step S5). That is, the contraction process shown in FIG. 4 for acquiring the darkest pixel in the 1 × h [pixel] region long in the y direction is performed, and then the expansion process shown in FIG. 5 for acquiring the brightest pixel is performed. As a result, as shown in FIG. 12, an image (hereinafter referred to as a second GSTH image) ID in which the white portion is extracted in the y direction and with a length of h or less is obtained. Note that h corresponds to the diameter of the hanger 6 and is calculated experimentally. In the example shown in FIG. 12, the second GSTH image I D is an image in which only the hangers 6 are extracted to the difference image I C.
The second GSTH image ID is input as a converted image to thehanger detector 31b via the memory 31c.
第二のGSTH画像IDは変換画像としてメモリ31cを経てハンガー検出部31bへ入力される。 Subsequently, the difference image I C is GSTH processed in the y direction in the
The second GSTH image ID is input as a converted image to the
続いて、ハンガー検出部31bにおいて、図12に示す第二のGSTH画像IDから、二値化処理等を使用してハンガー6を検出する(ステップS6)。架設されているハンガー6は所定の等間隔(距離)で設置されているので、検出したハンガー6の数を計数し画像中の位置を把握する。
Subsequently, the hanger detection unit 31b, the second GSTH image I D shown in FIG. 12, for detecting the hanger 6 using binarization process or the like (step S6). Since the installed hangers 6 are installed at predetermined equal intervals (distances), the number of detected hangers 6 is counted to grasp the position in the image.
以上のステップP1~ステップP6の処理を全てのラインセンサ画像Iの入力が終了するまで行う。
The above processing from Step P1 to Step P6 is performed until the input of all the line sensor images I is completed.
このように構成される本実施例に係る画像処理によるハンガー検出装置では、GSTH処理は図4に示した収縮処理と図5に示した膨張処理を組み合わせて、かつ、w×1[pixel]と1×h[pixel]の領域から直線を求めることで、輝度反転画像IA中に写る直線のなかから所定の方向で、かつ所定の太さより細い直線だけを抽出することができる。
そのため、本実施例に係る画像処理によるハンガー検出装置にはGSTHの特徴を生かした次の利点がある。
・所定の方向と所定の太さで写るハンガー6だけを検出できる。
・トンネル坑口や電柱7などハンガー6とは異なる特徴を有する外乱7を排除しハンガー6だけを検出できる。
・本実施例では鉛直方向に設置された正常なハンガー6のみを検出し、設置角度が管理値外の正常でない斜めのハンガー6は検出しない。そのため、本実施例で検出したハンガー6の本数と、予め設備データとして管理されている電柱ごとの正常なハンガー6の本数とを比較することで、異常なハンガー6を検出することもできる。 In the hanger detection apparatus using image processing according to the present embodiment configured as described above, the GSTH processing is a combination of the shrinkage processing shown in FIG. 4 and the expansion processing shown in FIG. By obtaining a straight line from the 1 × h [pixel] area, it is possible to extract only a straight line that has a predetermined direction and is thinner than a predetermined thickness from the straight lines that appear in the luminance inverted image I A.
Therefore, the hanger detection apparatus using image processing according to the present embodiment has the following advantages that make use of the features of GSTH.
-Only thehanger 6 reflected in a predetermined direction and a predetermined thickness can be detected.
-Only thehanger 6 can be detected by eliminating the disturbance 7 having characteristics different from those of the hanger 6 such as the tunnel wellhead and the utility pole 7.
In the present embodiment, onlynormal hangers 6 installed in the vertical direction are detected, and abnormal hangers 6 whose installation angles are outside the control value are not detected. Therefore, the abnormal hanger 6 can also be detected by comparing the number of hangers 6 detected in the present embodiment with the number of normal hangers 6 for each utility pole that is managed in advance as facility data.
そのため、本実施例に係る画像処理によるハンガー検出装置にはGSTHの特徴を生かした次の利点がある。
・所定の方向と所定の太さで写るハンガー6だけを検出できる。
・トンネル坑口や電柱7などハンガー6とは異なる特徴を有する外乱7を排除しハンガー6だけを検出できる。
・本実施例では鉛直方向に設置された正常なハンガー6のみを検出し、設置角度が管理値外の正常でない斜めのハンガー6は検出しない。そのため、本実施例で検出したハンガー6の本数と、予め設備データとして管理されている電柱ごとの正常なハンガー6の本数とを比較することで、異常なハンガー6を検出することもできる。 In the hanger detection apparatus using image processing according to the present embodiment configured as described above, the GSTH processing is a combination of the shrinkage processing shown in FIG. 4 and the expansion processing shown in FIG. By obtaining a straight line from the 1 × h [pixel] area, it is possible to extract only a straight line that has a predetermined direction and is thinner than a predetermined thickness from the straight lines that appear in the luminance inverted image I A.
Therefore, the hanger detection apparatus using image processing according to the present embodiment has the following advantages that make use of the features of GSTH.
-Only the
-Only the
In the present embodiment, only
〔簡略化したGSTH処理を用いたハンガー検出装置:GSTH(gsth(A))〕
以下、図1から図6及び図8から図13を用いて本発明の実施例2に係る画像処理によるハンガー検出装置について説明する。本実施例に係る画像処理によるハンガー検出装置は、GSTH処理部31aにおける処理が簡略化されている点が実施例1とは異なる。装置構成については実施例1に係る画像処理によるハンガー検出装置と同様であり、以下、重複する説明は省略し、画像処理部3における処理を中心に説明する。 [Hanger detector using simplified GSTH treatment: GSTH (gsth (A))]
Hereinafter, a hanger detection apparatus using image processing according to the second embodiment of the present invention will be described with reference to FIGS. 1 to 6 and FIGS. 8 to 13. The hanger detection apparatus using image processing according to the present embodiment is different from the first embodiment in that the processing in theGSTH processing unit 31a is simplified. The apparatus configuration is the same as that of the hanger detection apparatus based on image processing according to the first embodiment, and the description thereof will be omitted below, focusing on the processing in the image processing unit 3.
以下、図1から図6及び図8から図13を用いて本発明の実施例2に係る画像処理によるハンガー検出装置について説明する。本実施例に係る画像処理によるハンガー検出装置は、GSTH処理部31aにおける処理が簡略化されている点が実施例1とは異なる。装置構成については実施例1に係る画像処理によるハンガー検出装置と同様であり、以下、重複する説明は省略し、画像処理部3における処理を中心に説明する。 [Hanger detector using simplified GSTH treatment: GSTH (gsth (A))]
Hereinafter, a hanger detection apparatus using image processing according to the second embodiment of the present invention will be described with reference to FIGS. 1 to 6 and FIGS. 8 to 13. The hanger detection apparatus using image processing according to the present embodiment is different from the first embodiment in that the processing in the
図13に基づいて、本実施例に係る画像処理によるハンガー検出装置における処理の流れを説明する。
図13に示すように、本実施例に係る画像処理によるハンガー検出装置おいては、まずラインセンサカメラ2から図8に一例を示すようなラインセンサ画像Iを入力し(ステップS11)、続いて、GSTH処理部31aにおいてラインセンサ画像Iに対してx方向で主成分の輝度値が淡色の撮影ラインについて輝度値を反転する処理を行う(ステップS12)。これにより、図9に示すような輝度反転画像IAを得る。 Based on FIG. 13, the flow of the process in the hanger detection apparatus by the image processing which concerns on a present Example is demonstrated.
As shown in FIG. 13, in the hanger detection apparatus using image processing according to the present embodiment, a line sensor image I as shown in FIG. 8 is first input from the line sensor camera 2 (step S11), and then In theGSTH processing unit 31a, the line sensor image I is subjected to a process of inverting the luminance value for a photographing line whose main component luminance value is light in the x direction (step S12). This gives inverted luminance image I A, as shown in FIG.
図13に示すように、本実施例に係る画像処理によるハンガー検出装置おいては、まずラインセンサカメラ2から図8に一例を示すようなラインセンサ画像Iを入力し(ステップS11)、続いて、GSTH処理部31aにおいてラインセンサ画像Iに対してx方向で主成分の輝度値が淡色の撮影ラインについて輝度値を反転する処理を行う(ステップS12)。これにより、図9に示すような輝度反転画像IAを得る。 Based on FIG. 13, the flow of the process in the hanger detection apparatus by the image processing which concerns on a present Example is demonstrated.
As shown in FIG. 13, in the hanger detection apparatus using image processing according to the present embodiment, a line sensor image I as shown in FIG. 8 is first input from the line sensor camera 2 (step S11), and then In the
続いて、同じくGSTH処理部31aにおいて、図8に示す輝度反転画像IAをx方向へgsth処理する(ステップS13)。すなわち、x方向に長いw×1[pixel]の領域内で最も暗い画素を取得する図4に示す収縮処理を施す一方、最も明るい画素を取得する図5に示す膨張処理は実施しない。これによって図11に示すような白色箇所がx方向について幅w以下で抽出されたgsth画像ICを得る。なおwはトロリ線4などの線条の幅に対応しており、実験的に算出する。
Subsequently, likewise in GSTH processing unit 31a, to gsth processing the luminance reversed image I A shown in FIG. 8 the x-direction (step S13). That is, the contraction process shown in FIG. 4 for acquiring the darkest pixel in the region of w × 1 [pixel] long in the x direction is performed, while the expansion process shown in FIG. 5 for acquiring the brightest pixel is not performed. As a result, a gsth image I C in which white portions as shown in FIG. 11 are extracted with a width w or less in the x direction is obtained. Note that w corresponds to the width of the strip such as the trolley wire 4 and is calculated experimentally.
続いて、同じくGSTH処理部31aにおいて、gsth画像ICをy方向へGSTH処理する(ステップS14)。すなわち、y方向に長い1×h[pixel]の領域内で最も暗い画素を取得する図4に示す収縮処理を施し、次に最も明るい画素を取得する図5に示す膨張処理を施す。これによって図12に示すように白色箇所が、y方向でかつh以下の長さで抽出されたGSTH画像IDを得る。なおhはハンガー6の直径に対応しており、実験的に算出する。
GSTH画像IDは変換画像としてメモリ31cを経てハンガー検出部31bへ入力される。 Subsequently, theGSTH processing unit 31a similarly performs GSTH processing on the gsth image I C in the y direction (step S14). That is, the contraction process shown in FIG. 4 for acquiring the darkest pixel in the 1 × h [pixel] region long in the y direction is performed, and then the expansion process shown in FIG. 5 for acquiring the brightest pixel is performed. As a result, as shown in FIG. 12, a GSTH image ID in which white portions are extracted in the y direction and with a length equal to or shorter than h is obtained. Note that h corresponds to the diameter of the hanger 6 and is calculated experimentally.
The GSTH image ID is input as a converted image to thehanger detector 31b via the memory 31c.
GSTH画像IDは変換画像としてメモリ31cを経てハンガー検出部31bへ入力される。 Subsequently, the
The GSTH image ID is input as a converted image to the
続いて、ハンガー検出部31bにおいて、図12に示すGSTH画像IDから、二値化処理等を使用してハンガー6を検出する(ステップS15)。ハンガー6は所定の間隔(距離)で設置されているので、検出したハンガー6を計数することで車両1の現在位置を把握し、また、ハンガー6の設置角度には管理値があるので、所定の設置角度かどうかを検査する。
Subsequently, the hanger detection unit 31b detects the hanger 6 from the GSTH image ID shown in FIG. 12 using binarization processing or the like (step S15). Since the hangers 6 are installed at a predetermined interval (distance), the current position of the vehicle 1 is grasped by counting the detected hangers 6, and the installation angle of the hangers 6 has a management value. Inspect whether the installation angle is.
以上のステップP11~ステップP15の処理を全てのラインセンサ画像Iの入力が終了するまで行う。
The above processing of Step P11 to Step P15 is performed until the input of all the line sensor images I is completed.
このように構成される本実施例に係る画像処理によるハンガー検出装置では、輝度反転画像IAをx方向へgsth処理する(図4に示した収縮処理のみを実施する)ことにより処理を簡略化しているので、実施例1に比べてハンガー検出処理を高速化できる利点がある。なお、gsth処理を行うことにより、画像上で検出されたハンガー6が短くはなるが、本実施例はハンガー6の有無の判定が目的であるので、検出したハンガー6が短くなっても影響はない。
In the hanger detection apparatus using image processing according to the present embodiment configured as described above, the luminance inversion image I A is subjected to gsth processing in the x direction (only the contraction processing shown in FIG. 4 is performed), thereby simplifying the processing. Therefore, there is an advantage that the hanger detection processing can be speeded up as compared with the first embodiment. Although the hanger 6 detected on the image is shortened by performing the gsth process, the present embodiment is intended to determine whether or not the hanger 6 is present. Absent.
本発明は、画像処理によるハンガー検出装置に適用して好適なものである。
The present invention is suitable for application to a hanger detection apparatus using image processing.
1 車両
2 ラインセンサカメラ
3 画像処理部
4 トロリ線
5 ちょう架線
6 ハンガー
7 構造物
31 演算装置
31a GSTH処理部
31b ハンガー検出部
31c メモリ
32 記録装置
I ラインセンサ画像
IA 輝度反転画像
IB 第一のGSTH画像
IC 差分画像,gsth画像
ID 第二のGSTH画像,GSTH画像 1vehicle 2 line sensor camera 3 image processing unit 4 trolley wire 5 messenger wire 6 Hanger 7 structure 31 arithmetic unit 31a GSTH processor 31b hanger detection unit 31c memory 32 recording device I line sensor image I A INVERSION image I B first GSTH image I C difference image, gsth image ID Second GSTH image, GSTH image
2 ラインセンサカメラ
3 画像処理部
4 トロリ線
5 ちょう架線
6 ハンガー
7 構造物
31 演算装置
31a GSTH処理部
31b ハンガー検出部
31c メモリ
32 記録装置
I ラインセンサ画像
IA 輝度反転画像
IB 第一のGSTH画像
IC 差分画像,gsth画像
ID 第二のGSTH画像,GSTH画像 1
Claims (4)
- 等間隔に設置されトロリ線を支持するハンガーを車両の屋根上から撮影するラインセンサカメラと、前記車両の内部に設置され前記ラインセンサカメラによって得られる画像を解析する画像処理部とを備えて前記画像中のハンガーを検出する画像処理によるハンガー検出装置であって、
前記画像処理部が、
前記ラインセンサカメラから入力されるラインセンサ画像に対して前記ラインセンサカメラの撮影ライン方向及び時間方向に順次GSTH処理を行って前記画像中の前記ハンガーを強調したGSTH画像を取得するGSTH処理部と、
前記GSTH画像からハンガーを検出するハンガー検出部と
を有することを特徴とする画像処理によるハンガー検出装置。 A line sensor camera for photographing a hanger that is installed at equal intervals and supports a trolley line from the roof of the vehicle, and an image processing unit that is installed inside the vehicle and analyzes an image obtained by the line sensor camera, A hanger detection device by image processing for detecting a hanger in an image,
The image processing unit
A GSTH processing unit that sequentially performs GSTH processing on a line sensor image input from the line sensor camera in a shooting line direction and a time direction of the line sensor camera to obtain a GSTH image in which the hanger in the image is emphasized; ,
A hanger detection device using image processing, comprising: a hanger detection unit for detecting a hanger from the GSTH image. - 前記GSTH処理部が、前記GSTH処理として、前記ラインセンサ画像に対し、前記ラインセンサカメラの撮影ライン方向について収縮処理を行った後膨張処理を行って第一のGSTH画像を取得し、前記ラインセンサ画像と前記第一のGSTH画像との差分を取って差分画像を取得し、前記差分画像に対し時間方向について収縮処理を行った後膨張処理を行って前記ラインセンサ画像中の前記ハンガーを強調した第二のGSTH画像を取得し、
前記ハンガー検出部が、前記第二のGSTH画像から前記ハンガーを検出する
ことを特徴とする請求項1記載の画像処理によるハンガー検出装置。 The GSTH processing unit obtains a first GSTH image by performing an expansion process on the line sensor image after performing a contraction process on the imaging line direction of the line sensor camera as the GSTH process, and acquiring the first GSTH image. A difference image is obtained by taking a difference between the image and the first GSTH image, and after the shrinkage process is performed on the difference image in the time direction, the expansion process is performed to emphasize the hanger in the line sensor image Get a second GSTH image,
The hanger detection apparatus according to claim 1, wherein the hanger detection unit detects the hanger from the second GSTH image. - 前記GSTH処理部が、前記GSTH処理として、前記ラインセンサ画像に対し、前記ラインセンサカメラの撮影ライン方向については収縮処理のみを行ってgsth画像を取得し、前記gsth画像に対し時間方向について収縮処理を行った後膨張処理を行って前記ラインセンサ画像中の前記ハンガーを強調した前記GSTH画像を取得し、
前記ハンガー検出部が、前記GSTH画像から前記ハンガーを検出する
ことを特徴とする請求項1記載の画像処理によるハンガー検出装置。 As the GSTH processing, the GSTH processing unit obtains a gsth image by performing only a contraction process on the line sensor image in the photographing line direction of the line sensor camera, and acquires a gsth image in the time direction on the gsth image. The GSTH image in which the hanger in the line sensor image is emphasized by performing an expansion process after performing
2. The hanger detection apparatus according to claim 1, wherein the hanger detection unit detects the hanger from the GSTH image. - 前記GSTH処理部が、前記ラインセンサ画像に対し、前記ラインセンサカメラの撮影ライン方向について1ラインずつ、当該撮影ライン方向で主成分の輝度値が淡色の場合は輝度値を反転し主成分の輝度値が濃色の場合は輝度値を反転しない輝度反転処理を行った後、前記GSTH処理を行う
ことを特徴とする請求項1から請求項3のいずれか1項に記載の画像処理によるハンガー検出装置。 The GSTH processing unit inverts the luminance value for the line sensor image, one line at a time for the shooting line direction of the line sensor camera, and the luminance value of the main component in the shooting line direction when the luminance value of the main component is light color. The hanger detection by image processing according to any one of claims 1 to 3, wherein when the value is a dark color, the GSTH process is performed after performing a luminance inversion process that does not invert the luminance value. apparatus.
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CN109019335B (en) * | 2018-09-04 | 2019-10-11 | 大连理工大学 | A kind of Hoisting Security distance detection method based on deep learning |
JP2020149286A (en) * | 2019-03-13 | 2020-09-17 | 株式会社明電舎 | Overhead wire fitting detection device and overhead wire fitting detection method |
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