This paper proposes a matched filtering edge detection method to overcome the weaknesses of traditional edge extraction methods, such as poor noise resistance, incomplete targets, and missing location information. Through this method, we can more effectively extract the edges of the target image, thereby obtaining extraction results with stronger edge-focusing ability.This method can effectively suppress the background, improve the integrity and accuracy of edge extraction.
In the field of machinery manufacturing, due to the backward detection methods of the outer dimensions of the workpiece, the high labor intensity of the detection and the high production cost, the problems of poor detection accuracy and low efficiency are caused. Therefore, this paper designs an industrial camera-based intelligent detection system for workpiece outer dimensions. The system uses industrial cameras to simulate human vision functions to accurately extract information from workpiece images and convert them into a form that can be understood and calculated by computers. Compared with the traditional manual workpiece external size detection method, the system has the advantages of good positioning flexibility, short sampling period, large amount of information, low cost, good stability, high precision and intelligence, etc., and the system realizes online non-contact detection, which has the characteristics of high accuracy, fast speed, and easy operation; at the same time, the system realizes the real-time measurement of the outer dimensions of the workpiece and the result output, and the detection accuracy is less than 0.01mm.Through the actual production environment test, the system can meet the requirements of rapid and accurate detection of the outer dimensions of the workpiece, and effectively enhance the ability of automatic manufacturing and detection of products.
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