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Nur Farah Afiqah Binti Mohd Yusof
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Computer Science & IT Economics, Econometrics & Finance

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Plant Disease Detection Using CBIR Nur Farah Afiqah Binti Mohd Yusof
Prosiding International conference on Information Technology and Business (ICITB) 2017: INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND BUSINESS (ICITB) 3
Publisher : Proceeding International Conference on Information Technology and Business

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Abstract

This paper represents a discussion about one of the usage of CBIR (content-based image retrieval) in our daily life. The agriculture field had developed tremendously in applying technology throughout the years. Farmers are now able to cope up the problems to produce the maximum production. In order to maximize the process, there are specific technologies that can help the farmers to recognize and prevent the plant diseases at early stage. If the process of recognition is done manually, it consumes a lot of human energy by examining each of the plant in a whole thousand hectares. So, researchers around the globe try to invent a system based on color, edges and histogram matching to identify the plant diseases. Furthermore, the data of trait is collected every time a new plant disease is detected. CBIR still lacks maturity, and is not yet being used on a significant scale. In the absence of hard evidence on the effectiveness of CBIR techniques in practice, opinion is still sharply divided about their usefulness in handling real-life queries in large and diverse image collections. Keyword: Content-based image retrieval (CBIR) systems, Color Histogram, Image processing, Image retrieval, Plant disease detection.
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