Detection method for scratches and defects on surfaces of metal components

Abstract

The invention discloses a detection method for scratches and defects on the surfaces of metal components. The detection method comprises the process steps of (1) obtaining the images of the surfaces of the metal components, and selecting a processing domain; (2) performing image processing and analysis on the surfaces of the metal components; and (3) automatically marking scratches and processing, wherein the step particularly comprises the following steps: 1, after the image analysis, segmenting and extracting the texture information of the scratches and the defects of the images by adopting an image segmentation method; 2, after the information of the scratches and the defects is extracted, performing scratch identification comprising image segmentation or object separation, characteristic extraction and selection, optimal decision classification making, and object determination; and 3, quantizing the scratches. According to the detection method disclosed by the invention, the steps of scratch and defect processing and partial algorithms are emphasized, and location, extraction and quantization for tiny scratches and defects can be performed; and the method is high in identification accuracy, objective in detection standards, and quantitative in description. Detection algorithms for the scratches and the defects exist in the form of plug-in, thus being convenient to be integrated in application software to update the software.

Description

technical field [0001] The invention relates to the field of machine vision, and in particular discloses a method for detecting scratches on the surface of metal parts. The method can accurately extract fine scratches. Background technique [0002] Machine vision is widely used in the fields of national economy, scientific research and national defense construction. Its biggest advantage is non-contact measurement. Compared with other methods, it has great advantages in safety, reliability, detection accuracy, detection speed and detection cost. In terms of surface defect detection, machine vision has a wide range of applications. There may be different degrees of defects on the surface of any metal parts, among which scratches are one of the common surface defects, which may seriously affect the quality of the product. The traditional detection of scratches on the surface of metal parts is done by human eyes, and there are many subjective factors and problems that can onl...

AI Technical Summary

Problems solved by technology

There may be different degrees of defects on the surface of any metal parts, among which scratches are one of the common surface defects, which may seriously affect the quality of the product

The traditional detection of scratches on the surface of metal parts is done by human eyes, and there are many subjective factors and problems that can only be judged qualitatively

In addition, the texture of scratches on the surface of some metal parts is weak and the degree of defects is small. It is difficult to recognize, classify and quantify them with human eyes. Therefore, it is imperative to automatically detect them based on vision.

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