Journal Title : International Journal of Modern Trends in Engineering and Science

Author’s Name : P Sangeetha | Dr N Suguna  unnamed

Volume 03 Issue 04 2016

ISSN no:  2348-3121

Page no: 5-7

Abstract – The value of paddy is strongly related to the quality, types and sizes of paddy without any damage or disease of that leaves. Hence detecting the disease or damage area of the leaf is very important to improve the utilization rate. Though the crop production is well grown there is still lagging in visual inspection of diseases. Although it is done manually, it is not accurate in all the times. So, there is a need for technique to detect the diseases. The system proposed is based on this method which can detect the diseases using artificial neural network concept. This system involves image acquisition, converting the RGB images into HSI image and morphological process for removing noise. The block level feature extraction is used for extracting the features like mean and standard deviation. Finally, it is classified based on the diseases using artificial neural network and support vector machine. For more accuracy, the stem cells samples can be used for detecting the disease.

Keywords— Image Acquisition; Grey level co-occurrence matrix; Artificial neural network; Support vector machine 


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