Recognition Method of Cotton Blind Stinkbug Hazard Level Based on Image Processing

Abstract:

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.

• Periodical: Applied Mechanics and Materials (Volumes 511-512)
• Pages: 481-489
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.511-512.481
• Online since: February 2014
• Authors: Jian Hua Zhang, Fan Tao Kong, Wei Chen*, Jian Zhai Wu, Meng Shuai Zhu
• Keywords: Hazard Level, Image Processing, Naïve Bayesian Classifier, Recognition

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