TY - JOUR
KW - Image Processing
KW - Classification
KW - Plan Disease
KW - Feature Selection
KW - Experimentation
AU - Jagadeesh D.Pujari
AU - Rajesh Yakkundimath
AU - Abdulmunaf. Syedhusain Byadgi
AB - Computers have been used for mechanization and automation in different applications of agriculture/horticulture. The critical decision on the agricultural yield and plant protection is done with the development of expert system (decision support system) using computer vision techniques. One of the areas considered in the present work is the processing of images of plant diseases affecting agriculture/horticulture crops. The first symptoms of plant disease have to be correctly detected, identified, and quantified in the initial stages. The color and texture features have been used in order to work with the sample images of plant diseases. Algorithms for extraction of color and texture features have been developed, which are in turn used to train support vector machine (SVM) and artificial neural network (ANN) classifiers. The study has presented a reduced feature set based approach for recognition and classification of images of plant diseases. The results reveal that SVM classifier is more suitable for identification and classification of plant diseases affecting agriculture/horticulture crops.
IS - Regular Issue
M1 - 7
N2 - Computers have been used for mechanization and automation in different applications of agriculture/horticulture. The critical decision on the agricultural yield and plant protection is done with the development of expert system (decision support system) using computer vision techniques. One of the areas considered in the present work is the processing of images of plant diseases affecting agriculture/horticulture crops. The first symptoms of plant disease have to be correctly detected, identified, and quantified in the initial stages. The color and texture features have been used in order to work with the sample images of plant diseases. Algorithms for extraction of color and texture features have been developed, which are in turn used to train support vector machine (SVM) and artificial neural network (ANN) classifiers. The study has presented a reduced feature set based approach for recognition and classification of images of plant diseases. The results reveal that SVM classifier is more suitable for identification and classification of plant diseases affecting agriculture/horticulture crops.
PY - 2016
SP - 6
EP - 14
T2 - International Journal of Interactive Multimedia and Artificial Intelligence
TI - SVM and ANN Based Classification of Plant  Diseases Using Feature Reduction Technique
UR - http://www.ijimai.org/journal/sites/default/files/files/2016/05/ijimai20163_7_1_pdf_75740.pdf
VL - 3
SN - 1989-1660
ER -