Detection method based on image fusion and detection apparatus therefor

Abstract

A detection method based on image fusion comprises the steps of: irradiating a to-be-detected object with a plurality of illuminating modules in different directions in order to obtain a plurality frames of to-be-detected images; performing image fusion treatment to the to-be-detected images; and performing feature screening to an obtained a texture image or a height image. The method not only canreduce influence due to poor image collection quality under low-contrast but also can provide complete surface feature information, which has advantages of fusing the surface feature information in each frame of the to-be-detected images into the texture image or height image and recognizing and screening the surface defect features from the distinguishing characteristics of the images. An apparatus, with combination of the surface defect detection method, can maximumly eliminate influence due to environmental factors during the detection on the to-be-detected object, and can synthesize and obtain the feature image, comprising the surface defect features from a large number of images. The method and apparatus enhance screening effect on the surface defect features and complete the surfacedefect detection operation under the low-contrast condition.

Description

technical field [0001] The invention relates to an image detection technology, in particular to a detection method based on image fusion and a detection device thereof. Background technique [0002] At present, in industries such as industrial materials and printed matter, in order to ensure product quality and remove waste products at high speed, machine vision technology is often used to detect the surface of the workpiece or the surface of the paper to find such as spots, pits, scratches, defects, embossed characters, Surface defects such as dirt, color difference, missing printing, ink diffusion, etc. The main method for surface defect detection is image model comparison. Image models are established through pre-selected standard image feature domains, and the current image to be detected is compared pixel by pixel with these image models to determine the difference value. defect features in the image. There is also a surface defect detection method using an image filt...

AI Technical Summary

Problems solved by technology

However, due to objective factors such as light source attenuation, light source shift, lens pollution, and inconsistent exposure parameters, problems such as inaccurate image models and poor image contrast often occur. Defect screening methods such as computing have certain requirements for image quality when processing images, and are not suitable for screening out defect features from low-contrast images.

Therefore, the existing technology cannot detect defects such as low-ratio wrinkles, spots, and color differences, so there are problems such as missed detection and false detection in the detection of surface defects.

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