Punched workpiece defect detection method based on image processing

A technology for stamping workpieces and defect detection. It is applied in image data processing, image enhancement, image analysis, etc., and can solve the problems of low detection efficiency, high cost, and poor repeatability.

Inactive Publication Date: 2015-11-18
XI'AN POLYTECHNIC UNIVERSITY
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Problems solved by technology

[0004] The purpose of the present invention is to provide a stamping workpiece defect detection method based on image processing, which solves the problems of high cost, poor repeatability and low detection efficiency of existing workpiece detection methods

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  • Punched workpiece defect detection method based on image processing
  • Punched workpiece defect detection method based on image processing
  • Punched workpiece defect detection method based on image processing

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Embodiment Construction

[0081] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0082] The process flow of a method for detecting stamping workpiece defects based on image processing in the present invention is as follows figure 1 As shown, the specific detection steps are:

[0083] Step 1, use the light source, high-definition CCD camera, and image acquisition card to obtain the image of the stamping workpiece, and use the adaptive voting fast median filter method to perform image denoising processing:

[0084] Step 1.1: Divide the acquired workpiece image into N×N filtering sliding windows, where N≥3, and N is an odd number;

[0085] Step 1.2: Scan the pixels in the filtering sliding window obtained in step 1.1 one by one, and set the pixel value of the center point x ij The pixel value θ of its neighboring pixels ab for comparison, when x ij = θ ab , vote for the gray value of the pixel; and judge x ij Whether i...

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Abstract

The present invention discloses a punched workpiece defect detection method based on image processing. The method comprises the concrete steps of obtaining a punched workpiece image and using an adaptive voting fast median filtering method to carry out image denoising processing, using Contourlet transform and a niche particle swarm optimization algorithm to carry out image enhancement and carrying out edge detection processing on the image, and finally carrying out punched workpiece defect detection. According to the method, the Contourlet transform and the niche particle swarm optimization algorithm are used to carry out image enhancement, the image overall contrast is raised, the edge detail of the workpiece image is enhanced, the repeatability of the workpiece detection is increased, for the characteristic that the defect part edge in the punched workpiece image is obvious, the invention provides an edge detection based on the integration of a neural network and a rapid fuzzy algorithm, and while the detection cost is reduced, the detection efficiency is greatly improved.

Description

technical field [0001] The invention belongs to the technical field of industrial production detection and detection, and in particular relates to a defect detection method of stamping workpieces based on image processing. Background technique [0002] Image detection technology is widely used in product detection at home and abroad. It is a comprehensive detection system based on optics and integrated with image processing technology, optoelectronic technology, computer technology and other contemporary advanced science and technology. This technology mainly uses optical technology to image the detected substance, uses the image as a carrier of information transmission or a means of detection, and then realizes the detection of the external characteristics of the material through certain processing. [0003] At present, most workpiece defect detection methods need to binarize the acquired workpiece image. This method has strict requirements on the light source, and the expe...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
CPCG06T7/0004G06T2207/20084G06T2207/20192G06T2207/30164
Inventor 王延年刘婷刘成涛张双双
Owner XI'AN POLYTECHNIC UNIVERSITY
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