基于增强内容的图像检索系统及病害蔬菜分类

N. Belsha, N. Hariprasad
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引用次数: 2

摘要

蔬菜在印度农业中发挥着重要作用,提供经济活力,营养安全,并很好地适应我国不同地区盛行的主要集约化种植制度。开发提高蔬菜质量和生产力的技术,解决日益增加的生物和非生物病害是蔬菜研究的主要挑战。蔬菜病害的鉴定与分类是农业科学中最重要和最受关注的研究课题。图像处理是分类检索系统中最合适和最好的工具。提出的工作是检索和分类各种类型的感染和未感染的蔬菜图像。介绍了一种基于内容的图像检索(CBIR)系统,该系统是在大型数据库中检索蔬菜图像进行质量分析的难点。将特征提取技术应用于植物图像的CBIR系统中。在对感染蔬菜的分类中是通过特征提取和分类的过程来完成的。最终结果为胡萝卜、土豆、甜椒、白菜、番茄等5种蔬菜的强化体系、染病蔬菜的侵染面积以及染病/未染病蔬菜的性能分析。
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The enhanced content based image retrieval system and classification of infected vegetables
Vegetables play a major role in Indian agriculture by providing economic viability, nutritional security, and fit well into the predominant intensive cropping systems prevailing in different parts of our country. To develop technologies that enhance quality and productivity of vegetables and solve increasing biotic and abiotic diseases is the major challenge in vegetable research. The vegetable disease identification and classification is the most important and catching attention research topic in the agriculture science. Image processing is the most suitable and best tool for classification and retrieval system. The Proposed work is to retrieve and classify the various types of infected and non-infected vegetable image. Searching the vegetable image from the large database for the analysis of the quality is difficult to defeat this Content-Based Image Retrieval (CBIR) system is introduced. A novel approach of CBIR system is used in the vegetable images by using feature extraction techniques. In classification of the infected vegetables is done through the process of feature extraction and classification. The final results shows for enhanced system of five types of vegetables like carrot, potato, bell pepper, Cabbage and tomato, Area of Infection of infected vegetable, and performance analysis of Infected/Non-infected vegetables.
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