CN111243016B - Automatic container identification and positioning method - Google Patents
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- CN111243016B CN111243016B CN201811501109.8A CN201811501109A CN111243016B CN 111243016 B CN111243016 B CN 111243016B CN 201811501109 A CN201811501109 A CN 201811501109A CN 111243016 B CN111243016 B CN 111243016B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
- G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
- G06T7/33—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods
- G06T7/337—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods involving reference images or patches
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
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Abstract
The invention discloses an automatic container identification and positioning method, which comprises an industrial personal computer, a binocular camera, a monocular camera and a light source, wherein a WinCC process monitoring system application program with an SQL Server database is installed on the industrial personal computer, the position information of the container number of a container is stored in the database, the WinCC process monitoring system is provided with a set of storage and warehousing programs, the binocular camera is installed on a container lifting appliance and is used for carrying out secondary identification and positioning on the container, the monocular camera is installed at a container warehousing place and is used for automatically identifying the container number in a warehouse, the light source and the camera are installed in a matched manner, and the brightness can be automatically adjusted according to the change of ambient light. According to the method, the theoretical position of the container is stored through the database, then the binocular camera is adopted to collect the pictures of the container, and a set of algorithm based on machine vision is designed to secondarily identify and position the container.
Description
Technical Field
The invention relates to the field of automation, in particular to an automatic container identification and positioning method.
Background
Along with the rapid development of logistics industry and the rise of labor cost, the wharf, port, goods yard and other places are urgently required to increase the goods turnover efficiency and reduce the labor management cost by improving the automation level of the machinery. The requirement on the operation of a driver is high in the link of lifting the container by the crane, and the time consumption is long when the lifting appliance is aligned to the container by adopting manual operation. The key to improving the efficiency of the link is to realize the automatic alignment of the lifting appliance and the lock hole on the container. With the progress of computer, image processing, artificial intelligence, intelligent control and other technologies, the flexible automation technology based on machine vision is realized and rapidly developed, and at present, the container identification and positioning technology based on machine vision has become a hot spot for the research of vast students.
Disclosure of Invention
In order to improve the mechanical automation level of wharfs, ports, goods yards and the like, the invention provides an automatic container identification and positioning method, which is realized by the following technical scheme:
the automatic container identifying and positioning method includes industrial computer, binocular camera, monocular camera and light source, and the industrial computer is equipped with WinCC process monitoring system application program with SQL Server data base, the binocular camera is mounted on container lifting tool, the monocular camera is mounted in container warehouse-in place, and the light source is mounted in combination with camera, and can automatically regulate brightness according to the change of ambient light. The method specifically comprises the following steps:
step 1: and respectively adjusting focal length and aperture of the binocular camera and the monocular camera, calibrating the binocular camera by adopting a Zhang plane calibration method to obtain internal and external parameters of the camera, and preparing for three-dimensional coordinate reconstruction.
Step 2: before the container is put in storage, the monocular camera scans and collects the container number pattern and uploads the pattern to the industrial personal computer, a set of automatic identification system for the container number is arranged on the industrial personal computer, the system automatically identifies and uploads the container number to a WinCC process monitoring system, the WinCC process monitoring system is provided with a set of storage in-out and in-out program, the program is used for draining and finding out empty positions of a site database, and an AGV (automatic guided vehicle) is used for automatically conveying the container to a destination nearby the empty positions.
Step 3: after the AGV guiding trolley conveys the container to a destination near the vacant site, a binocular camera on the container lifting tool collects the container picture and uploads the container picture to an industrial personal computer, a set of automatic container identification and positioning algorithm is designed in the industrial personal computer, the collected pattern is analyzed, the accurate position of a container lock hole is identified, the container lifting tool automatically punches and lifts the container to place the vacant site, meanwhile, a WinCC process monitoring system stores the position information of the container number in an SQL Server database, the AGV trolley automatically returns to an entrance and exit, and the container warehousing is completed. When the container is delivered, firstly, searching an SQL Server database according to the container number of the container to be delivered, finding out the position information corresponding to the container number, automatically enabling a container crane to reach the position, collecting the container image delivered by a binocular camera on a container lifting tool, uploading the container image to an industrial personal computer, carrying out secondary judgment on the container information by a container automatic identification and positioning algorithm in the industrial personal computer, carrying out perforation after the accurate position is identified, lifting the container to be placed on an AGV trolley to be delivered to an outlet, and deleting the position information of the container number by the database, thereby completing delivery.
In the step 3, the position of the container stored in the SQL Server database is a theoretical value and has a certain deviation from the actual position, so that the binocular camera is adopted to secondarily identify and position the container, and the accurate position of the lock hole on the container is found out, and the specific algorithm is as follows:
step 3.1: the binocular camera collects container patterns, a multi-operator fusion algorithm is adopted for the container edge extraction aiming at the patterns, noise reduction processing is carried out on the extracted edges, container edge coordinates are extracted, the relative offset angle of the container and the binocular camera is calculated, photographing is carried out again after the offset angle is zero by rotating the lifting appliance, new edge coordinates of the patterns after noise reduction are obtained, redundant backgrounds are removed by utilizing the coordinates, and a container image is intercepted.
Step 3.2: and (3) carrying out threshold processing on the cut container image, cutting out a keyhole image on the container, carrying out feature matching on the keyhole positions of the left image and the right image which are cut out, removing points which do not accord with the matching by utilizing the Euclidean distance method, and calculating the center pixel coordinate of the keyhole.
Step 3.3: and carrying out three-dimensional reconstruction on the central pixel coordinates of the lock hole, bringing the internal and external parameters marked by the camera into a projection matrix, and obtaining the central world coordinates of the lock hole according to simultaneous equations of the central pixel coordinates of the lock hole of the left and right images and the projection matrix.
Compared with the prior art, the invention has the following obvious advantages: the mechanical automation level of wharfs, ports, goods yards and other places is improved, and the efficiency of hoisting containers by a crane is improved. Firstly, the theoretical position of the container is stored in a database, and secondly, the container is secondarily identified and positioned by adopting a machine vision algorithm, so that the positioning precision is improved, the image background interference is reduced, and the algorithm is simple in processing, high in efficiency and strong in applicability.
Drawings
Fig. 1 is a flow chart of the operation of the present invention.
Detailed Description
The following further describes the implementation of the present invention:
the automatic container identifying and positioning method includes industrial computer, binocular camera, monocular camera and light source, and the industrial computer is equipped with WinCC process monitoring system application program with SQL Server data base, and the binocular camera is mounted on the container lifting tool for secondary identification and positioning of container, and the monocular camera is mounted on the container warehouse-in place for automatic identification of warehouse-in container number, and the light source is mounted together with camera, and can automatically regulate brightness according to the change of ambient light.
The method specifically comprises the following steps:
step 1: and respectively adjusting focal length and aperture of the binocular camera and the monocular camera, calibrating the binocular camera by adopting a Zhang plane calibration method to obtain internal and external parameters of the camera, and preparing for three-dimensional coordinate reconstruction.
Step 2: before the container is put in storage, the monocular camera scans and collects the container number pattern and uploads the pattern to the industrial personal computer, a set of automatic identification system for the container number is arranged on the industrial personal computer, the system automatically identifies and uploads the container number to a WinCC process monitoring system, the WinCC process monitoring system is provided with a set of storage in-out and in-out program, the program is used for draining and finding out empty positions of a site database, and an AGV (automatic guided vehicle) is used for automatically conveying the container to a destination nearby the empty positions.
Step 3: after the AGV guiding trolley conveys the container to a destination near the vacant site, a binocular camera on the container lifting tool collects the container picture and uploads the container picture to an industrial personal computer, a set of automatic container identification and positioning algorithm is designed in the industrial personal computer, the collected pattern is analyzed, the accurate position of a container lock hole is identified, the container lifting tool automatically punches and lifts the container to place the vacant site, meanwhile, a WinCC process monitoring system stores the position information of the container number in an SQL Server database, the AGV trolley automatically returns to an entrance and exit, and the container warehousing is completed. When the container is delivered, firstly, searching an SQL Server database according to the container number of the container to be delivered, finding out the position information corresponding to the container number, automatically enabling a container crane to reach the position, collecting the container image delivered by a binocular camera on a container lifting tool, uploading the container image to an industrial personal computer, carrying out secondary judgment on the container information by a container automatic identification and positioning algorithm in the industrial personal computer, carrying out perforation after the accurate position is identified, lifting the container to be placed on an AGV trolley to be delivered to an outlet, and deleting the position information of the container number by the database, thereby completing delivery.
In the step 3, the position of the container stored in the SQL Server database is a theoretical value and has a certain deviation from the actual position, so that the binocular camera is adopted to secondarily identify and position the container, and the accurate position of the lock hole on the container is found out, and the specific algorithm is as follows:
step 3.1: the binocular camera collects container patterns, a multi-operator fusion algorithm is adopted for the container edge extraction aiming at the patterns, noise reduction processing is carried out on the extracted edges, container edge coordinates are extracted, the relative offset angle of the container and the binocular camera is calculated, photographing is carried out again after the offset angle is zero by rotating the lifting appliance, new edge coordinates of the patterns after noise reduction are obtained, redundant backgrounds are removed by utilizing the coordinates, and a container image is intercepted.
Step 3.2: and (3) carrying out threshold processing on the cut container image, cutting out a keyhole image on the container, carrying out feature matching on the keyhole positions of the left image and the right image which are cut out, removing points which do not accord with the matching by utilizing the Euclidean distance method, and calculating the center pixel coordinate of the keyhole.
Step 3.3: and carrying out three-dimensional reconstruction on the central pixel coordinates of the lock hole, bringing the internal and external parameters marked by the camera into a projection matrix, and obtaining the central world coordinates of the lock hole according to simultaneous equations of the central pixel coordinates of the lock hole of the left and right images and the projection matrix.
In the design of the automatic container identification and positioning method, the theoretical position of the container is firstly stored in the database, and then the container is secondarily identified and positioned by adopting the machine vision algorithm, so that the positioning precision is improved, the image background interference is reduced, and the algorithm is simple in processing, high in efficiency and strong in applicability.
The technical means disclosed by the scheme of the invention is not limited to the technical means disclosed by the embodiment, and also comprises the technical scheme formed by any combination of the technical features. It should be noted that modifications and adaptations to the invention may occur to one skilled in the art without departing from the principles of the present invention and are intended to be within the scope of the present invention.
Claims (1)
1. A container automatic identification and positioning method is characterized in that: the system comprises an industrial personal computer, a binocular camera, a monocular camera and a light source, wherein a WinCC process monitoring system application program with an SQL Server database is installed on the industrial personal computer, the binocular camera is installed on a container lifting appliance, the monocular camera is installed at a container warehouse entry position, and the light source is installed in a matched manner with the camera and can automatically adjust brightness according to the change of ambient light; the method specifically comprises the following steps:
step 1: the focal length and aperture of the binocular camera and the monocular camera are adjusted respectively, the binocular camera is calibrated by adopting a Zhang plane calibration method, internal and external parameters of the camera are obtained, and preparation is made for three-dimensional coordinate reconstruction;
step 2: before a container is put in storage, a monocular camera scans and collects container number patterns and uploads the container number patterns to an industrial personal computer, a set of automatic container number recognition system is arranged on the industrial personal computer, the automatic container number recognition system carries out automatic recognition uploading to a WinCC process monitoring system, the WinCC process monitoring system is provided with a set of storage in-out program, the program carries out arrangement and space searching on a site database, and an AGV guide trolley automatically conveys the container to a destination nearby the space;
step 3: after the AGV guides the trolley to transport the container to the destination near the vacancy, the binocular camera on the container sling collects the container picture and uploads to the industrial personal computer, a set of container automatic identification and positioning algorithm is designed in the industrial personal computer, the collected pattern is analyzed, the accurate position of the container lock hole is identified, the container sling automatically punches and lifts the container to place the vacancy, meanwhile, the WinCC process monitoring system stores the position information of the container number in the SQL Server database, the AGV trolley automatically returns to the entrance and exit, and the container warehousing is completed;
when the container is delivered, firstly searching an SQL Server database according to the container number of the container to be delivered, finding out the position information corresponding to the container number, automatically reaching the position by a container crane, wherein the position of the container stored in the SQL Server database is a theoretical value and has a certain deviation from the actual position, so that a binocular camera is adopted to secondarily identify and position the container, and the accurate position of a lock hole on the container is found out;
the method comprises the following specific steps: the binocular camera on the container sling collects the pictures of the container coming out of the warehouse and uploads the pictures to the industrial personal computer, the automatic identification and positioning algorithm of the container in the industrial personal computer carries out secondary judgment on the information of the container, the container is placed on the AGV trolley to be delivered to the outlet after the accurate position of the lock hole of the container is identified, and meanwhile, the database deletes the position information of the number of the container to finish the coming out of the warehouse;
the specific algorithm for identifying the accurate position of the lock hole of the container is as follows:
step 3.1: the binocular camera collects container patterns, a multi-operator fusion algorithm is adopted for the container edge extraction of the patterns, noise reduction treatment is carried out on the extracted edges, container edge coordinates are extracted, the relative offset angle of the container and the binocular camera is calculated, photographing is carried out again after the offset angle is zero by rotating a lifting appliance, new edge coordinates of the patterns after noise reduction are obtained, redundant backgrounds are removed by utilizing the coordinates, and a container image is intercepted;
step 3.2: performing threshold processing on the cut container image, cutting out a keyhole image on the container, performing feature matching on the keyhole positions of the left image and the right image, removing points which do not accord with the matching by using the Euclidean distance method, and calculating the center pixel coordinate of the keyhole;
step 3.3: and carrying out three-dimensional reconstruction on the central pixel coordinates of the lock hole, bringing the internal and external parameters marked by the camera into a projection matrix, and obtaining the central actual coordinates of the lock hole according to simultaneous equations of the central pixel coordinates of the lock hole of the left and right images and the projection matrix.
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Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112288800B (en) * | 2020-09-27 | 2023-05-12 | 山东浪潮科学研究院有限公司 | Method, equipment and device for identifying door lock eyes of server cabinet |
| CN114219842B (en) * | 2021-12-14 | 2022-08-12 | 东南大学 | Visual identification, distance measurement and positioning method in port container automatic loading and unloading operation |
| CN114339989B (en) * | 2021-12-27 | 2023-04-28 | 同济大学 | Multi-agent system distributed positioning method based on azimuth angle |
| CN115049322B (en) * | 2022-08-16 | 2022-12-20 | 安维尔信息科技(天津)有限公司 | Container management method and system for container yard |
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