期刊
JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION
卷 37, 期 -, 页码 70-77出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jvcir.2015.04.005
关键词
Strip steel defect image; Mathematical morphology; Genetic algorithm; Image binarization; Non-uniform illumination; EOBMM; Top-hat transformation; Fitness function; Genetic operations
资金
- National Natural Science Foundation of China [61100133]
- Hubei Province Key Laboratory Open Foundation [znss2013B014]
In order to precisely extract the image shape feature for the defect detection and classification, the strip steel image needs to firstly be binarized effectively. In this paper, the intelligent information processing, including mathematical morphology and genetic algorithm, is introduced to the strip steel defect image binarization. In order to eliminate the effect of non-uniform illumination and enhance the detailed information of the strip steel defect image, an enhancement operator based on mathematical morphology (EOBMM) is proposed firstly. And then, the binarization method based on genetic algorithm (BMBGA) is applied to the binarization of the strip steel defect image processed by EOBMM. The experiment results show that our method is effective and efficiency in the strip steel defect image binarization and outperforms the traditional image binarization methods, Otsu and Bernsen. (C) 2016 Published by Elsevier Inc.
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