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Method for acquiring visual multi-target robust template of industrial component

A multi-target and template technology, applied in the field of image processing, can solve the problems of inaccurate reference maps and templates, and achieve the effects of saving time in finding templates, good position accuracy, and improving efficiency

Active Publication Date: 2021-04-02
常州微亿智造科技有限公司
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Problems solved by technology

[0007] The technical problem to be solved by the present invention is to provide a method for obtaining a robust multi-target visual template for industrial components, and to solve the problems of batch matching based on multiple templates and multiple targets, and inaccurate reference maps and templates in the existing situation

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  • Method for acquiring visual multi-target robust template of industrial component
  • Method for acquiring visual multi-target robust template of industrial component
  • Method for acquiring visual multi-target robust template of industrial component

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[0042] In order to make the technical problems, technical solutions and beneficial effects solved by the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0043] See figure 1 , a method for obtaining robust templates for industrial parts vision multi-target, the specific steps are as follows:

[0044]The first step, the selection of the optimal reference image: in order to achieve 100% batch detection, it is necessary to select the optimal reference image as the template image, and a total of n acquisition images have been collected, n is a positive integer greater than 1, that is, there are n acquisition images Images, including collected image 1, collected image 2...collected image n, select the optimal reference image ...

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Abstract

The invention discloses a method for acquiring a visual multi-target robust template of an industrial part, and the method comprises the steps: selecting an optimal reference image: totally collectingn collection images, selecting the optimal reference image from the n collection images, and selecting an area with a larger pixel value gradient change from the n collection images; selecting a multi-target robust template: searching a matching template with better robustness on the basis of the optimal reference image, and enabling the matching template to be correctly matched on all corresponding images; and searching similar images: traversing the obtained matching template on the original image, calculating the Euclidean distance between the matching template and the corresponding pixelpoint on the target image, and finding an area similar to the template on other images. According to the method, batch detection can be realized, and a template with relatively good robustness can befound by 100%, the searched template is optimal in location degree and can completely contain the target, and the target is located in the middle of the template; and the operation speed of the processing process is high, parallel processing and multi-thread technologies are adopted, the time for searching the template is saved, and the efficiency is improved.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a method for acquiring robust templates for visual multi-targets of industrial components. Background technique [0002] Image matching is a classic technique of image processing, and it is an algorithm based on statistical ideas, which has a wide range of applications in computer vision, pattern recognition and industrial inspection. Template matching is a method for finding the target image modelImage (template image) in the source image srcImage. Its principle is to measure the similarity between two images through some similarity criteria (srcImage, modelImage). The existing image matching algorithms can be mainly divided into three categories: image matching methods based on gray information, image matching methods based on edge information and image matching methods based on features. [0003] In the field of machine vision industrial inspection, defect detection ...

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Application Information

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IPC IPC(8): G06K9/62
CPCG06V10/751G06F18/22
Inventor 邱增帅王罡潘正颐侯大为
Owner 常州微亿智造科技有限公司
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