Strip Steel Target Detection Algorithm Based on Single Image Rapid Defog and Morphological Interframe Difference

摘要

In the production process of strip steel, detecting wave edge in real time is quite important, otherwise it willcontribute to the abandonment of strip steel materials. At this stage, an automatic identification system based on machinevision which aims to figure out the wave edge of strip steel is gradually being put into use. However, it is shown that thecomplicated environment of the factory makes it difficult to reach its goals. In order to solve this problem, this paperdesigns a motion strip steel target detection algorithm based on single image rapid defog and morphological interframedifference. Firstly, based on the physical model of foggy image degradation, using a simple mean filtering to estimate theenvironmental light and global atmospheric light, thus the removal of water mist in video screen is realized. Then, usinginterframe differential method to extract the motion strip steel in the image, and the noise is filtered by masksegmentation and morphological operator. At last, the experimental results show that the optimization algorithm is moreaccurate and effective compared with the traditional motion target detection algorithm.