SMS Based HPCCDD Algorithm for the Identification of Leaf Spot Diseases

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 221)

Abstract

Advance computing techniques Capitalized as Mobile base identification of cotton diseases and control of pest, using Automatic system for rural area farmers. This technology base farm management system is Capitalized to identify and analyze the diseases, profitability, sustainability and safety for the land resource. The sharing of plant physical condition knowledge on a regional basis can support both crop manufacture and trade. In this model of work, a new computing technology has been proposed to help the farmer to take a superior decision concerning several aspects of the crop manufacturing process. Suitable evaluation and diagnosis of crop diseases in the field is very critical for the increased production. Foliar is the most important fungal disease of cotton and occurs in all growing Indian cotton regions. In this work we express technological strategies using mobile captured symptoms of cotton leaf spot images and classify the diseases using neural network. This system can identify diseases and provide pest recommendation to farmers.

Keywords

HPCCDD algorithm Cotton leaves spot diseases Mobile camera Capture Image process 

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Copyright information

© Springer India 2013

Authors and Affiliations

  1. 1.Department of Software SystemKarpagamUniversityCoimbatorIndia

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