DocumentCode :
721201
Title :
A study on agricultural image processing along with classification model
Author :
Chahal, Neetu
Author_Institution :
Deptt. Of Comput. Sc., ITM Univ., Gurgaon, India
fYear :
2015
fDate :
12-13 June 2015
Firstpage :
942
Lastpage :
947
Abstract :
Agricultural image processing is one of most innovative and important image processing areas recognized in last few years. Because of the vast range of associated sub domain it is having the current attention of the researchers. In this paper, the exploration of different domains associated with agricultural image processing is defined. The paper has also explored the recognition model with broader view. The paper has presented a generalized framework for plant disease classification and recognition. The paper has also defined a study on some of the effective classification approaches including SVM, Neural Network, KMeans and PCA.
Keywords :
agriculture; diseases; image classification; neural nets; principal component analysis; support vector machines; KMeans; PCA; SVM; agricultural image processing; classification approaches; classification model; neural network; plant disease classification; plant disease recognition; recognition model; Agriculture; Diseases; Feature extraction; Image segmentation; Neural networks; Soil; Agricultural; Land Featured set; Leaf; Plant;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advance Computing Conference (IACC), 2015 IEEE International
Conference_Location :
Banglore
Print_ISBN :
978-1-4799-8046-8
Type :
conf
DOI :
10.1109/IADCC.2015.7154843
Filename :
7154843
Link To Document :
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