Image processing techniques for grading & classification of rice

Author

Verma, Bhupinder

Author_Institution

Dept. of ECE, Lovely Prof. Univ. Phagwara, Phagwara, India

fYear

2010

fDate

17-19 Sept. 2010

Firstpage

220

Lastpage

223

Abstract

A relatively faster computer vision system has been discussed to analyze and sort rice kernels. A series of measurements were done using image processing techniques on three varieties of Indian rice namely Markfed Supreme, Markfed Golden (export quality), Hafed Basmati. Area, perimeter, maximum length, maximum width, compactness and elongation were measured. Further, separating the rice varieties by their shape difference was examined. The computer vision system developed has been able to sort rice into sound, cracked, chalky, broken and damaged kernels with an accuracy ranging from 90-95%.

Keywords

area measurement; computer vision; crops; length measurement; Hafed Basmati rice; Indian rice; Markfed golden rice; Markfed supreme rice; area measurement; compactness measurement; computer vision system; elongation measurement; image processing technique; maximum length measurement; maximum width measurement; perimeter measurement; rice classification; rice grading; rice kernel sorting; Artificial neural networks; Classification algorithms; Feature extraction; Head; Image analysis; Kernel; Magnetic heads; Binarization Morphological operations; Computer/Machine vision; Image anafysis; Neural Networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Communication Technology (ICCCT), 2010 International Conference on

Conference_Location

Allahabad, Uttar Pradesh

Print_ISBN

978-1-4244-9033-2

Type

conf

DOI

10.1109/ICCCT.2010.5640428

Filename

5640428