Arecanut grading based on three sigma controls and SVM

Author

Danti, Ajit ; Suresha, M.

Author_Institution

Dept. of Comput. Applic., Jawaharlal Nehru Nat. Coll. of Eng., Shimoga, India

fYear

2012

fDate

30-31 March 2012

Firstpage

372

Lastpage

376

Abstract

In this paper, effective grading of arecanuts is proposed. The Arecanut RGB image is converted into YC_BC_R color space. Three sigma control limits on color features are determined for effective segmentation of arecanuts. Color features are used for the grading of arecants with the help of support vector machines (SVMs) into two grades i.e. Boiling and Non-boiling nuts effectively. Experimental k-fold cross validation method demonstrated the efficiency of the proposed approach.

Keywords

agriculture; crops; feature extraction; image colour analysis; image segmentation; support vector machines; Arecanut RGB image; Arecanut grading; India; SVM; YC_BC_R color space; arecanut segmentation; boiling nuts; color features; commercial crops; k-fold cross validation method; nonboiling nuts; support vector machines; three sigma controls; Aerospace electronics; Educational institutions; Humans; Image color analysis; Indexes; Kernel; Support vector machines; Arecanut; classification; segmentation; sigma control limits; support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Advances in Engineering, Science and Management (ICAESM), 2012 International Conference on

Conference_Location

Nagapattinam, Tamil Nadu

Print_ISBN

978-1-4673-0213-5

Type

conf

Filename

6215627