Paper
3 January 2020 Strip steel target detection algorithm based on single image rapid defog and morphological interframe difference
Author Affiliations +
Proceedings Volume 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019); 113732E (2020) https://doi.org/10.1117/12.2557250
Event: Eleventh International Conference on Graphics and Image Processing, 2019, Hangzhou, China
Abstract
In the production process of strip steel, detecting wave edge in real time is quite important, otherwise it will contribute to the abandonment of strip steel materials. At this stage, an automatic identification system based on machine vision which aims to figure out the wave edge of strip steel is gradually being put into use. However, it is shown that the complicated environment of the factory makes it difficult to reach its goals. In order to solve this problem, this paper designs a motion strip steel target detection algorithm based on single image rapid defog and morphological interframe difference. Firstly, based on the physical model of foggy image degradation, using a simple mean filtering to estimate the environmental light and global atmospheric light, thus the removal of water mist in video screen is realized. Then, using interframe differential method to extract the motion strip steel in the image, and the noise is filtered by mask segmentation and morphological operator. At last, the experimental results show that the optimization algorithm is more accurate and effective compared with the traditional motion target detection algorithm.
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Miao Peng, Peifeng Hao, Zijun Peng, and Caihua Yang "Strip steel target detection algorithm based on single image rapid defog and morphological interframe difference", Proc. SPIE 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019), 113732E (3 January 2020); https://doi.org/10.1117/12.2557250
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KEYWORDS
Detection and tracking algorithms

Image processing

Image filtering

Image segmentation

Visual process modeling

Image processing algorithms and systems

Target detection

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