期刊
SIGNAL IMAGE AND VIDEO PROCESSING
卷 10, 期 2, 页码 379-388出版社
SPRINGER LONDON LTD
DOI: 10.1007/s11760-015-0751-y
关键词
Android; Human mobile interaction (HMI); Multi-resolution and multi-directional transform; Mobile disease diagnosis system; Pattern recognition; Plant leaf
资金
- SURA, IIT Roorkee
The process of detecting plant disease by human naked-eye is difficult and very expensive practice, particularly in developing countries like India. Designing and providing a fast-reliable automated mobile vision based solution for such tasks, is a great realistic contribution to the society. In this paper, a mobile client-server architecture for leaf disease detection and diagnosis using a novel combination of Gabor wavelet transform (GWT) and gray level co-occurrence matrix (GLCM), opens a new dimension in pattern recognition, is proposed. Mobile disease diagnosis system represents a diseased patch in multi-resolution and multi-direction feature vector. Mobile client captures and pre-processes the leaf image, segments diseased patches in it and transmits to the Pathology Server, reducing transmission cost. The Server performs the computational tasks: GWT-GLCM feature extraction and -Nearest Neighbor classification. The result is sent back to the users screen via an SMS (short messaging service) with an accuracy rate of 93 %, in best condition. On the other part, paper also focus on design of Human-mobile interface (HMI), which is useful even for the illiterate farmers, to automatically monitor their field at any stage by just a mobile click. Android is currently used to run this system which can be easily extended to other mobile operating systems.
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