Recognition method of cotton blind stinkbug hazard level based on image processing

文献类型： 外文期刊

第一作者： Zhang, Jianhua

作者： Zhang, Jianhua;Zhu, Mengshuai;Kong, Fantao;Chen, Wei;Wu, Jianzhai

作者机构：

关键词： Keywords Image processing;Hazard level;Recognition;Naive Bayesian classifier

期刊名称：SENSORS, MECHATRONICS AND AUTOMATION

ISSN： 1660-9336

年卷期： 2014 年 511-512 卷

页码：

收录情况： SCI

摘要： In view of complex background of cotton blind stinkbug hazard region and the difficulty in segmentation and classification under natural conditions, an automatic classification method of cotton blind stinkbug hazard level was proposed. In this method, crop regions and disease regions of cotton were extract respectively by H+a*+b* component and Otsu segmentation method based on blind stinkbug hazard cotton leaves. Adhesion cotton leaves separated by Watershed segmentation method and cotton leaf area hazard by blind stinkbug extracted. According to cotton blind the stinkbug hazard rating standard, combination Naive Bayes classifier and color, texture and shape features extracted from images to classify the hazard rating of the blind stinkbug. The results showed that the model classification correct rate was 90.0%, it could classify the hazard rating of the cotton blind stinkbug and provide technical support for the prevention and treatment of the cotton blind stinkbug.

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