Surface defect detection algorithm based on machine vision

Abstract

The invention discloses a surface defect detection algorithm based on machine vision. After images of an object surface are collected, an extreme value filter difference algorithm is adopted for massive defects, and a linear reinforced detector algorithm is adopted for scratch defects. According to the algorithm, the online detection requirement can be met by adopting conventional hardware configuration, and the characteristics of good real-time performance and quantitative production line operation can be achieved; and the characteristics of defect shape and the like are taken into consideration, so that a good defection effect is achieved, and the method is applicable to various different searches can be reinforced. The algorithm can overcome instability, non-qualified production and lowefficiency state of existing surface defect vision detection technology.

Description

technical field [0001] The invention belongs to the field of digital image processing and image pattern recognition, in particular to a method for detecting image defects on object surfaces. Background technique [0002] With the improvement of living standards and the development of manufacturing technology, people have put forward higher requirements for product quality. 3C parts, processed parts, textiles, pharmaceutical packaging, food packaging and other industries all have product appearance quality inspection problems. Usually people pay attention to the quality of product appearance, mainly including: (1) products whose value depends on the quality of product appearance, such as printing, packaging, handicrafts, etc.; (2) products whose surface defects directly affect the use of products and deep processing, will It will bring great losses to users and deep processing customers. Therefore, it is very necessary to control the quality of products with surface defects. ...

AI Technical Summary

Problems solved by technology

[0003] At present, there is no mature online detection solution for surface defect detection of products in China; the detection equipment imported from abroad is not only expensive, but usually cannot be customized according to the specific needs of customers

However, traditional manual detection methods have great limitations in practical use.

First of all, manual detection relies on people's subjective evaluation, which is greatly unstable, unreliable and non-quantifiable due to the influence of people's mood, thinking and subjective and objective factors of lighting.

Brings many unstable and unreliable factors to the quality control of products

Secondly, the human eye cannot realize the real-time detection requirements during high-speed production of products. Therefore, it is necessary to study efficient automatic optical detection algorithms.

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