JPH03259706A - Appearance inspecting device - Google Patents
Appearance inspecting deviceInfo
- Publication number
- JPH03259706A JPH03259706A JP2059056A JP5905690A JPH03259706A JP H03259706 A JPH03259706 A JP H03259706A JP 2059056 A JP2059056 A JP 2059056A JP 5905690 A JP5905690 A JP 5905690A JP H03259706 A JPH03259706 A JP H03259706A
- Authority
- JP
- Japan
- Prior art keywords
- image
- value
- density gradient
- picture elements
- insulator
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000005856 abnormality Effects 0.000 claims abstract description 20
- 230000002159 abnormal effect Effects 0.000 claims abstract description 10
- 238000011156 evaluation Methods 0.000 claims description 17
- 238000001514 detection method Methods 0.000 claims description 12
- 230000000007 visual effect Effects 0.000 claims description 6
- 230000010365 information processing Effects 0.000 claims description 5
- 238000011179 visual inspection Methods 0.000 claims description 4
- 239000012212 insulator Substances 0.000 abstract description 10
- 238000006243 chemical reaction Methods 0.000 abstract description 2
- 230000001788 irregular Effects 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 12
- 238000007689 inspection Methods 0.000 description 12
- 238000000034 method Methods 0.000 description 11
- 230000004069 differentiation Effects 0.000 description 6
- 238000012544 monitoring process Methods 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 230000000694 effects Effects 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- 238000012937 correction Methods 0.000 description 1
- 230000001186 cumulative effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000012447 hatching Effects 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Landscapes
- Length Measuring Devices By Optical Means (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
- Image Processing (AREA)
- Image Analysis (AREA)
Abstract
Description
この発明は、例えば移動ロボットによる変電所などの巡
視点検において、一方向に濃度の繰り返しがある被検査
物体、例えば碍子等の外観異常を検査する外観検査装置
に関するものである。The present invention relates to an appearance inspection device for inspecting an abnormality in the appearance of an object to be inspected, such as an insulator, whose concentration repeats in one direction, for example, during a patrol inspection of a substation or the like using a mobile robot.
第11図は、例えば特開昭62−147888号公報に
示された従来の画像監視方式の回路構成図を示すもので
、図において16は照度変化検知方式設定回路、17は
照度計、18は前記照度計17の変化を計算によって求
める照度変化計算回路、19はヒストグラム作成回路、
20は複数の画素の連続変化を判定する連続変化判定回
路、2〕は予め記憶した標準パターン22と変化物体の
切出しデータや投影計算のデータを比較して変化物体の
識別を行う変化物体照合識別回路、23ば基準画像を現
画像に更新する基準画像更新回路、24は画素毎の変化
の大きさを設定値R1で検定し、それより大きな変化画
素のみを投影計算回路によりX、Yの各座標と平行な各
ライン毎に累月n算して投影する画素変化検定回路であ
る。
次に、第12図を参照して動作について説明する。
異常変化を検出しようとする場合には予め撮像しておい
た検査領域の画像を基準画像(第12図(a))として
記憶装置に格納しておき、検査時に撮像した画像(第1
2図(b))との差分処理を行い異常部分の検出(第1
2図(C))を行う。
次に、第11図の細部動作について説明する。
光学的手段をもって異常の検出を行うために、従来の発
明の場合には照度変化に対して正規化された画像比較を
行う。また、照度変化を異常変化と見なさず再度画像比
較して背景の基準画像を更新する方法を構じている。第
11図では照度変化の兆候を検出する方法として3種類
採用し、夫々の方式切、換は照度変化検知方式設定回路
16で行っている。前記3種類のうち第1の方式は照度
計17の出力変化を照度変化計算回路18で求めて行う
方式であり、第2の方式は照度計17の出力変化を照度
変化計算回路18の演算によってヒストグラム作成回路
19で形成する方式、又、第3の方式は複数の画素の連
続変化を判定する連続変化判定回路20を用いる方式で
ある。このよう比して照度変化に伴う補正を充分行った
後で、現画像と基準画像とを比較判定している。すなわ
ち、第1の方式の場合には、例えば照度変化量が設定値
より大きい場合に基準画像更新回路23で規準画像と置
き換えることによって判定を行う。第2の方式の場合に
はヒストグラムによる照度変化の検知を行い、画素変化
検定回路24で画素変化を検出してから変化物体照合識
別回路21で標準パターン22と比較して判定している
。また、第3の方式は連続変化判定回路20において設
定値R7以上に連続的な変化の回数があると判定された
場合に異常変化と判定して警報を発し、設定値R7より
少い回数の変化であれば、照度変化の兆しありと判定し
て基準画像を更新する指令を基準画像更新回路23に与
え基準画像を現画像に改めてから検知している。FIG. 11 shows a circuit configuration diagram of a conventional image monitoring system disclosed in, for example, Japanese Unexamined Patent Publication No. 62-147888. an illuminance change calculation circuit that calculates the change in the illuminance meter 17; 19 is a histogram creation circuit;
20 is a continuous change determination circuit that determines continuous changes in a plurality of pixels; 2] is a changing object matching/identification circuit that identifies a changing object by comparing cutout data and projection calculation data of the changing object with a standard pattern 22 stored in advance; A circuit 23 is a reference image updating circuit for updating the reference image to the current image, and 24 is a reference image updating circuit for updating the reference image to the current image; This is a pixel change verification circuit that calculates and projects the cumulative number n for each line parallel to the coordinates. Next, the operation will be explained with reference to FIG. When attempting to detect abnormal changes, an image of the inspection area taken in advance is stored in the storage device as a reference image (Fig. 12(a)), and an image taken during the examination (the first
Perform differential processing with Figure 2 (b)) to detect an abnormal part (first
2 (C)). Next, detailed operations in FIG. 11 will be explained. In order to detect an abnormality using optical means, in the case of the conventional invention, normalized image comparison is performed with respect to changes in illuminance. In addition, a method is provided in which the images are compared again and the reference image of the background is updated without regarding the change in illumination as an abnormal change. In FIG. 11, three methods are employed for detecting signs of illuminance change, and each method is switched by an illuminance change detection method setting circuit 16. Among the three types, the first method calculates the change in the output of the illuminance meter 17 using the illuminance change calculating circuit 18, and the second method calculates the change in the output of the illuminance meter 17 by calculating the change in the illuminance change calculating circuit 18. The histogram is formed by a histogram creation circuit 19, and the third method is a method using a continuous change determination circuit 20 that determines continuous changes in a plurality of pixels. After making sufficient corrections due to illuminance changes in this manner, the current image and the reference image are compared and judged. That is, in the case of the first method, for example, when the amount of change in illuminance is larger than a set value, the reference image updating circuit 23 performs the determination by replacing the image with a reference image. In the case of the second method, a change in illuminance is detected using a histogram, a pixel change verification circuit 24 detects a pixel change, and a changed object comparison/identification circuit 21 compares it with a standard pattern 22 to make a determination. In addition, in the third method, when the continuous change determination circuit 20 determines that the number of continuous changes is greater than or equal to the set value R7, it is determined that the change is abnormal and an alarm is issued; If there is a change, it is determined that there is a sign of a change in illuminance, and a command to update the reference image is given to the reference image update circuit 23, and the reference image is changed to the current image and then detected.
従来の画像監視方式は以上のように構成されているので
、基準画像と検査時画像との間で位置ずれや大きさの変
化があると、正常部分が誤って検出されやすく、両画像
間の正確な位置、大きさ合わせを必要とする等の課題が
あった。
この発明は、上記のような課題を解消するためになされ
たもので、被検出物の入力画像の正確な位置や大きさ合
わせを必要とせず、異常部分のみを検出することができ
る外観検査装置を得ることを目的とする。Conventional image monitoring systems are configured as described above, so if there is a positional shift or change in size between the reference image and the inspection image, a normal part is likely to be detected incorrectly, and the difference between the two images There were issues such as the need for accurate positioning and size matching. This invention was made to solve the above-mentioned problems, and provides a visual inspection device that can detect only abnormal parts without requiring accurate positioning or size adjustment of the input image of the object to be detected. The purpose is to obtain.
この発明に係る外観検査装置は被検査物体を視覚装置で
撮像し、その画像信号を量子化する量子化画像入力手段
と、その画像信号の各画素を予め定められた方向の濃度
勾配として求める濃度勾配検出手段と、その濃度勾配の
方向成分の絶対値が一定値以上の画素について濃度勾配
に垂直な方向の画素数を計数して投影変換する計数手段
と、その投影変換されたデータに対し前記計数値が所定
のしきい値以上の領域をエツジ領域と決めて評価値を求
める情報処理手段と、その評価値を予め記憶手段に格納
ずみの許容値と比較し、評価値が許容誤差を越えると異
常箇所有りとして検出する異常検出手段とを備え、被検
査物体の異常を自動的に検出するようにしたものである
。The appearance inspection apparatus according to the present invention includes a quantized image input means for capturing an image of an object to be inspected with a visual device and quantizing the image signal, and a density for determining each pixel of the image signal as a density gradient in a predetermined direction. a gradient detecting means, a counting means for counting and projecting the number of pixels in a direction perpendicular to the density gradient for pixels for which the absolute value of the direction component of the density gradient is equal to or greater than a certain value; an information processing means that determines an area where the count value is equal to or greater than a predetermined threshold value as an edge area and calculates an evaluation value, and compares the evaluation value with a tolerance value stored in advance in the storage means, and the evaluation value exceeds the tolerance error. and an abnormality detecting means for detecting the presence of an abnormal part, so that abnormalities in the object to be inspected are automatically detected.
この発明における外観検査装置は、視覚装置で撮像して
入力画像信号より一定方向に濃度勾配を持つ方向成分の
絶対値が所定値以上の画素について濃度勾配に垂直な方
向の画素数を計数して投影変換し、その投影像のピーク
値や所定位置の幅、ピーク値間距離、正負エツジ間距離
の評価値を求めて許容誤差値と比較し被検査物体の異常
検出を行うので、被検査物体の特徴量が強調され画像中
の対象物に位置や大きさの変化があっても確実に異常を
検出する。The appearance inspection device according to the present invention captures an image with a visual device and counts the number of pixels in a direction perpendicular to the density gradient for pixels whose absolute value of a direction component having a density gradient in a certain direction is equal to or greater than a predetermined value from an input image signal. Projection conversion is performed, and the peak value of the projected image, the width of a predetermined position, the distance between peak values, and the evaluation value of the distance between positive and negative edges are obtained and compared with the allowable error value to detect abnormalities in the inspected object. The feature values are emphasized to reliably detect abnormalities even if there are changes in the position or size of the object in the image.
以下、この発明の一実施例を図について説明する。
第1図は、この発明の一実施例を示す概略図である。図
において、1は移動ロボット、2はカメラ、3は被検査
物体の例えば碍子である。変電所や発電所において、移
動ロボット1が検査場所まで移動し、碍子3の外観を自
動的に検査する。
また、第2図はこの発明の一実施例を示すシステム構成
図である。図において、4は視覚装置2からの出力信号
を取込む画像入力手段、5ば予め決められた方向の濃度
勾配を求めるための濃度勾配検出手段としての方向性微
分回路、6は濃度勾配の絶対値が一定以上の画素を前記
濃度勾配に垂直な方向に計数し、投影データを得る計数
手段としての投影データ生成回路、7は前記投影データ
の特徴より外観の異常を検出する異常検出手段、8は異
常評価値の計算、その他を実行する情報処理手段として
のプロセッサ、9は記憶手段、10は外観検査装置であ
る。
また、第3図は外観を検査するための動作順序を示すフ
ローチャートである。大略、移動ロホッ1−1は所定の
位置まで移動した後で検査対象の碍子3をカメラ2で撮
像する。第4図は入力画像の一例である。
以上、第3図のフローチャートを参照して動作について
説明する。
まず、最初に移動ロボンi ]は所定の位置まで移動す
る。そして、検査対象の碍子3をカメラ2で撮像しディ
ジタルの画像入力データを外観検査装置10の画像入力
手段4に取込む(ステップ5Tl)。第4図は入力画像
の一例である。その人力画像より碍子3のヒダ方向(図
では上方から下方に)の濃度勾配を検出して方向成分を
抽出する。
そのために一定の方向性を持った方向性微分回路5で第
5図に示すように微分処理を行う(ステップ5T2)。
例えばヒダが水平の場合には、第6図(C)に示す様な
微分オペレータを用いる。この微分オペレータばヒダ等
のエツジの正負方向成分を検出できればよい。第6図の
場合、(a)のハツチングは対象物の画像を示すもので
、例えば、同図(C)の微分オペレータで微分処理を施
す。同図(a)のXl、Yl、Zlの3線上での濃度勾
配は、同図(b)のX2.Y2.Z2の方向性微分回路
の電気信号で、符号は方向性、濃度は濃度勾配の強さを
表わす。従って、方向性微分回路5は正負方向成分を検
出可能なオペレータであればよい。この微分画像に対し
微分値の絶対値が所定のしきい値以上の画素について正
負別々にヒダと平行な方向の画素数を投影データ生成回
路(計数手段)6によって計数する(ステップ5T3)
。正常時は、第7図にも示したように規則性のある投影
データが得られるが、第8図に示すように異常がある場
合には、その投影データも第9図(a) (b)(c)
に示すように規則性を失う(ステップ5T4)。
そこでこの投影データにだいし、異常検出手段7により
計数値nが所定のしきい値以上の領域をヒダのエツジ領
域とし、第10図に示すようにピーク(値)座標PRj
(nRj+ yRj) + pt、t (nLJ
+yy)と、ピーク値yR2,yLjにたいし所定の高
さにおける投影像の幅WRj、WLj算出をプロセッサ
8によって行う(ステップ5T5)、さらにピーク座標
間距離1)++i= (nRJ n++a++)+
DLJ−(n Lj n Lj。1)と、正負のエツ
ジ間距離H4を同様にプロセッサ8によって求め、(1
)式の値を評価値とし、異常の検出を行う(ステップS
T6〜5T9)。
そして、予め記憶手段9に格納された夫々の許容誤差が
例えば、ピーク座標間距離D、ピーク値y、投影像の幅
W、正負のエツジ間距離I]と(1)式の検出値とを比
較する(ステップ5TIO)。例えば(1)式の評価値
がすべて所定の容認誤差を越えないならば正常と評価し
、容認誤差を越えた場合には、異常箇所として検出する
(ステップ5T11)。
またこれらの評価値に対し、ファジー関数等の評価関数
を当てはめ、異常評価するようにしてもよい。
尚、本実施例では、碍子の検査について説明したが、階
段、梯子、電線等の同一方向成分が繰り返される物体に
ついても、同様に適用できる。
0An embodiment of the present invention will be described below with reference to the drawings. FIG. 1 is a schematic diagram showing an embodiment of the present invention. In the figure, 1 is a mobile robot, 2 is a camera, and 3 is an object to be inspected, such as an insulator. At a substation or power plant, a mobile robot 1 moves to an inspection location and automatically inspects the appearance of an insulator 3. Further, FIG. 2 is a system configuration diagram showing an embodiment of the present invention. In the figure, 4 is an image input means for receiving an output signal from the visual device 2, 5 is a directional differentiation circuit as a density gradient detection means for determining the density gradient in a predetermined direction, and 6 is the absolute value of the density gradient. a projection data generation circuit as a counting means for counting pixels having a value of a certain value or more in a direction perpendicular to the density gradient to obtain projection data; 7 is an abnormality detection means for detecting an abnormality in appearance from the characteristics of the projection data; 8; 1 is a processor serving as an information processing means for calculating an abnormality evaluation value and performing other operations; 9 is a storage means; and 10 is an appearance inspection device. Further, FIG. 3 is a flowchart showing the sequence of operations for inspecting the appearance. Roughly speaking, the mobile roof 1-1 images the insulator 3 to be inspected with the camera 2 after moving to a predetermined position. FIG. 4 is an example of an input image. The operation will now be described with reference to the flowchart shown in FIG. First, the mobile robot i moves to a predetermined position. Then, the insulator 3 to be inspected is imaged by the camera 2, and digital image input data is taken into the image input means 4 of the visual inspection apparatus 10 (step 5Tl). FIG. 4 is an example of an input image. The density gradient in the direction of the folds of the insulator 3 (from the top to the bottom in the figure) is detected from the human image, and the directional component is extracted. For this purpose, differentiation processing is performed using the directional differentiation circuit 5 having a certain directionality as shown in FIG. 5 (step 5T2). For example, if the folds are horizontal, a differential operator as shown in FIG. 6(C) is used. This differential operator only needs to be able to detect positive and negative direction components of edges such as folds. In the case of FIG. 6, the hatching in (a) indicates an image of the object, which is subjected to differentiation processing using, for example, the differential operator shown in FIG. 6(C). The concentration gradient on the three lines Xl, Yl, and Zl in Figure (a) is the same as the concentration gradient on the X2. Y2. This is an electrical signal from the directional differential circuit of Z2, where the sign represents the directionality and the concentration represents the strength of the concentration gradient. Therefore, the directional differentiation circuit 5 only needs to be an operator capable of detecting positive and negative direction components. The projection data generation circuit (counting means) 6 counts the number of pixels in the direction parallel to the folds, separately for positive and negative, for pixels whose absolute value of the differential value is greater than or equal to a predetermined threshold value for this differential image (step 5T3).
. Under normal conditions, regular projection data can be obtained as shown in Fig. 7, but if there is an abnormality as shown in Fig. 8, the projection data will also be obtained as shown in Fig. 9 (a) (b). )(c)
The regularity is lost as shown in (Step 5T4). Therefore, based on this projection data, the abnormality detection means 7 sets the area where the count value n is more than a predetermined threshold as the fold edge area, and the peak (value) coordinate PRj is set as shown in FIG.
(nRj+ yRj) + pt, t (nLJ
+yy), and the widths WRj, WLj of the projected image at a predetermined height are calculated by the processor 8 for the peak values yR2, yLj (step 5T5), and the distance between the peak coordinates 1)++i= (nRJ n++a++)+
DLJ-(n Lj n Lj.1) and the distance H4 between positive and negative edges are similarly determined by the processor 8, and (1
) is used as the evaluation value, and an abnormality is detected (step S
T6-5T9). Then, the respective allowable errors stored in advance in the storage means 9, for example, the distance between peak coordinates D, the peak value y, the width W of the projected image, the distance between positive and negative edges I] and the detected value of equation (1). Compare (Step 5TIO). For example, if all the evaluation values of equation (1) do not exceed a predetermined tolerance, it is evaluated as normal, and if they exceed the tolerance, it is detected as an abnormality (step 5T11). Further, an evaluation function such as a fuzzy function may be applied to these evaluation values to perform abnormality evaluation. In this embodiment, the inspection of insulators has been described, but the present invention can be similarly applied to objects such as stairs, ladders, and electric wires in which components in the same direction are repeated. 0
以上のように、この発明によれば視覚装置で被検査物体
を撮像して画像信号を量子化する画像入力手段と、その
画像信号から一定方向の濃度勾配を求める濃度勾配検出
手段と、その濃度勾配の方向成分の画素数を投影変換す
る計数手段と、その投影変換されたデータに対して特徴
部分の評価値を求める情報処理手段と、その評価値を許
容誤差と比較して異常箇所を検出する異常検出手段とを
もって外観検査装置を構成したので、被検査物体の特徴
が強調され信頼度の高い検査結果が得られる効果がある
。また、投影値を用いて検査を行うため、画像中での大
きさ変化にも容易に対処できるため、正確な位置決めを
必要とせず、機構部が簡便となって安価にできる効果が
ある。
更に異常判別のための評価基準を複数化したため、信頼
度が向上する効果がある。As described above, according to the present invention, there is provided an image input means for capturing an image of an object to be inspected using a visual device and quantizing an image signal, a concentration gradient detection means for calculating a concentration gradient in a certain direction from the image signal, and a concentration gradient detection means for determining a concentration gradient in a certain direction from the image signal. A counting means for projecting the number of pixels of the direction component of the gradient, an information processing means for calculating an evaluation value of a characteristic part from the projection-transformed data, and detecting an abnormal point by comparing the evaluation value with a tolerance error. Since the visual inspection apparatus is configured with the abnormality detection means, the features of the object to be inspected are emphasized and highly reliable inspection results can be obtained. In addition, since the inspection is performed using projection values, it is possible to easily deal with changes in size in the image, so there is no need for accurate positioning, and the mechanism is simple and inexpensive. Furthermore, since there are multiple evaluation criteria for abnormality determination, reliability is improved.
第1図はこの発明による外観検査装置の一実施例を示す
概略図、第2図はこの発明の一実施例によるハードウェ
アの構成を示すブロック図、第3図は外観異常を検出す
るための処理手順を示す説明図、第4図は入力画像の一
例を示す説明図、第5図は方向性微分画像の説明図、第
6図(a)(b) (C)は水平エツジ成分を検出する
微分オペレータの説明図、第7図は第5図の画像を水平
方向に画素数を計数した投影データ図、第8図は異常時
の入力画像説明図、第9図(a) (b)(c)は第8
図の投影データ説明図、第10図は異常検出のための評
価基準の説明図、第11図は従来の画像監視方式のハー
ドウェアの構成を示すブロック図、第12図は従来の画
像監視方式の原理を示すモデル図である。
図において、2はカメラ(視覚装置)、4は画像入力手
段、5は方向性微分回路(濃度勾配検出手段)、6ば投
影データ生成回路(計数手段)、7は異常検出手段、8
はプロセッサ(情報処理手段)、9は記憶手段。
なお、図中、同一符号は同一、又は相当部分を示す。FIG. 1 is a schematic diagram showing an embodiment of an appearance inspection device according to the present invention, FIG. 2 is a block diagram showing a hardware configuration according to an embodiment of the invention, and FIG. An explanatory diagram showing the processing procedure, Fig. 4 is an explanatory diagram showing an example of an input image, Fig. 5 is an explanatory diagram of a directional differential image, and Figs. 6 (a), (b), and (C) are horizontal edge components detected. Figure 7 is a projection data diagram of the image in Figure 5 that counts the number of pixels in the horizontal direction. Figure 8 is an illustration of the input image at abnormal times. Figure 9 (a) (b) (c) is the 8th
Fig. 10 is an explanatory diagram of evaluation criteria for abnormality detection, Fig. 11 is a block diagram showing the hardware configuration of a conventional image monitoring system, and Fig. 12 is a conventional image monitoring system. It is a model diagram showing the principle of. In the figure, 2 is a camera (visual device), 4 is an image input means, 5 is a directional differentiation circuit (density gradient detection means), 6 is a projection data generation circuit (counting means), 7 is an abnormality detection means, 8
9 is a processor (information processing means), and 9 is a storage means. In addition, in the figures, the same reference numerals indicate the same or equivalent parts.
Claims (1)
化する画像入力手段と、前記画像信号の各画素において
一定方向の濃度勾配を求める濃度勾配検出手段と、前記
濃度勾配の正負方向成分の絶対値が一定以上の画素につ
いて濃度勾配に垂直な方向の画素数を計数して投影変換
する計数手段と、前記投影変換されたデータに対し、前
記計数値が所定のしきい値以上の領域をエッジ領域と決
めて評価値を求める情報処理手段と、前記評価値を予め
記憶手段に格納ずみの許容値と比較し、該評価値が許容
誤差を越えると異常箇所として検出する異常検出手段と
を備えた外観検査装置。an image input means for capturing an image of an object to be inspected with a visual device and quantizing the image signal; a concentration gradient detection means for determining a concentration gradient in a fixed direction in each pixel of the image signal; a counting means for projectively converting pixels by counting the number of pixels in a direction perpendicular to the density gradient for pixels whose absolute values are above a certain value; an information processing means that determines an evaluation value for the edge region; and an abnormality detection means that compares the evaluation value with an allowable value stored in advance in a storage means and detects an abnormal location if the evaluation value exceeds the allowable error. Equipped with visual inspection equipment.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP2059056A JPH03259706A (en) | 1990-03-09 | 1990-03-09 | Appearance inspecting device |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP2059056A JPH03259706A (en) | 1990-03-09 | 1990-03-09 | Appearance inspecting device |
Publications (1)
Publication Number | Publication Date |
---|---|
JPH03259706A true JPH03259706A (en) | 1991-11-19 |
Family
ID=13102297
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
JP2059056A Pending JPH03259706A (en) | 1990-03-09 | 1990-03-09 | Appearance inspecting device |
Country Status (1)
Country | Link |
---|---|
JP (1) | JPH03259706A (en) |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104483326A (en) * | 2014-12-19 | 2015-04-01 | 长春工程学院 | High-voltage wire insulator defect detection method and high-voltage wire insulator defect detection system based on deep belief network |
CN109405771A (en) * | 2018-12-29 | 2019-03-01 | 西南交通大学 | A kind of contactless hierarchical detection method of top insulation sublist surface roughness |
CN109801284A (en) * | 2019-01-25 | 2019-05-24 | 华中科技大学 | A kind of high iron catenary insulator breakdown detection method based on deep learning |
-
1990
- 1990-03-09 JP JP2059056A patent/JPH03259706A/en active Pending
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104483326A (en) * | 2014-12-19 | 2015-04-01 | 长春工程学院 | High-voltage wire insulator defect detection method and high-voltage wire insulator defect detection system based on deep belief network |
CN109405771A (en) * | 2018-12-29 | 2019-03-01 | 西南交通大学 | A kind of contactless hierarchical detection method of top insulation sublist surface roughness |
CN109801284A (en) * | 2019-01-25 | 2019-05-24 | 华中科技大学 | A kind of high iron catenary insulator breakdown detection method based on deep learning |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
JP3279479B2 (en) | Video monitoring method and device | |
CN112232279B (en) | Personnel interval detection method and device | |
US10997702B2 (en) | Inspection apparatus, inspection method, and computer readable recording medium storing inspection program | |
JP2017049676A (en) | Posture discrimination device and object detection device | |
CN112307912A (en) | Method and system for determining personnel track based on camera | |
CN113888510A (en) | Detection method, detection device, detection equipment and computer readable storage medium | |
JPH04198741A (en) | Shape defect detecting device | |
US11145048B2 (en) | Image processing apparatus, image processing method, and non-transitory computer-readable storage medium for storing program | |
JPH03259706A (en) | Appearance inspecting device | |
JP4172236B2 (en) | Facial image processing apparatus and program | |
JP4552409B2 (en) | Image processing device | |
JPH02127393A (en) | Object position detecting device | |
JPH03255302A (en) | Detecting apparatus for pattern | |
US20230083531A1 (en) | Three-dimensional measuring device, and three-dimensional measuring method | |
JPH05113315A (en) | Detecting method for center position of circular image data | |
CN113330275B (en) | Camera information calculation device, camera information calculation system, camera information calculation method, and recording medium | |
JPH1091788A (en) | Device for positioning pattern and method therefor | |
JPH0383474A (en) | Car detector | |
JPH0399211A (en) | Recognition of body | |
JP2003016459A (en) | Method for detecting visual field direction deviation | |
JP3087788B2 (en) | Component position detection method and device | |
JPH03154173A (en) | Defective deciding image processor | |
JPS62221077A (en) | Pattern detector | |
KR950000493B1 (en) | Method of detecting semiconductor pellet | |
JP2986902B2 (en) | Image processing device |