Workpiece apparent defect detection method based on machine vision

A technology of appearance defect and detection method, which is applied in the direction of instrumentation, image data processing, calculation, etc., and can solve the problems of high false detection of the system, poor detection effect of small scratches, indentations and blistering defects, etc.

Active Publication Date: 2016-12-07
XIANGTAN UNIV
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Problems solved by technology

[0005] At present, the main methods of visual detection of workpiece appearance defects: (1) The automatic detection of metal workpiece surface defects is realized through genetic algorithm and visual image processing morphology. The bubble defect detection e

Method used

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  • Workpiece apparent defect detection method based on machine vision
  • Workpiece apparent defect detection method based on machine vision
  • Workpiece apparent defect detection method based on machine vision

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Embodiment 1

[0102] Such as figure 1 , a method for detecting workpiece appearance defects based on machine vision, comprising the following steps:

[0103] Step 1: Work piece image acquisition and preprocessing;

[0104] Step 2: Image segmentation and workpiece pose correction;

[0105] Step 3: Inspect for the following cosmetic defects: nicks, sticks, cracks, indentations, pinholes, scratches, and blisters.

[0106] In step 1, the workpiece image f(x, y) is collected by using the CCD industrial camera and the image acquisition card through the coaxial light source, and the workpiece image is a grayscale image, and then the workpiece image is sent to the industrial computer for preprocessing, and the preprocessing is Perform median filter processing on the collected workpiece images to remove the noise that may be caused during image capture and transmission, and improve the image signal-to-noise ratio.

[0107] In step 2:

[0108] (1) Image segmentation:

[0109] Segment the preproc...

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Abstract

The invention discloses a workpiece apparent defect detection method based on machine vision. Firstly, a visual system is used for guiding a robot, the pose of a target workpiece is precisely positioned according to a template matching algorithm based on a gray value, and then workpiece apparent defect detection is carried out and comprises the steps that firstly, a workpiece image is acquired and pretreated through median filtering; secondly, the target workpiece is divided through a global threshold value, and workpiece pose correction is carried out; thirdly, burr interference of the edge of the workpiece is removed through mathematical morphology open operation; fourthly, notches, material sticking, cracking, indentation, needle eyes, scratches and foaming apparent defects are detected. The method solves the problems that the artificial detection speed is slow, the efficiency is low and precision is poor; the problems that according to current vision detection, defect types are singular, the imaging quality is poor, and the false drop rate is high are solved, and the automation degree of precise workpiece production and product quality are improved.

Description

technical field [0001] The invention belongs to the field of automatic detection, in particular to a method for detecting workpiece appearance defects based on machine vision. Background technique [0002] The main production process of metal workpieces is machining, stamping, precision casting, powder metallurgy, metal injection molding, dimensional inspection, appearance defect inspection, etc. Affected by the manufacturing process throughout the production process, the size and appearance of the workpiece will be unqualified to a certain extent. Among them, appearance defects mainly include: gaps, sticky materials, cracks, indentations, pinholes, scratches and blisters, etc. If workpieces with appearance quality defects flow into the next production process, the assembly will be blocked and deformed, which will affect the quality of the assembled parts. potential economic losses and reputational risks. [0003] Traditional appearance defect inspection methods include m...

Claims

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Application Information

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IPC IPC(8): G06T7/00
CPCG06T7/0004G06T2207/20036G06T2207/20056G06T2207/30164
Inventor 许海霞王伟周维朱江莫言印峰周帮王倪东彭思齐王仕果
Owner XIANGTAN UNIV
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