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