An Intelligent system for identification of Indian Lentil types using Artificial Neural Network (BPNN)

Narendra, V G and Abdorrazzaghi, Muhammad (2013) An Intelligent system for identification of Indian Lentil types using Artificial Neural Network (BPNN). IOSR Journal of Computer Engineering (IOSRJCE), 15 (5). pp. 54-60. ISSN ISSN: 2278-0661

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Abstract

Lentils are designated into two classes, Red Lentils and Lentils other than red. The method of determining the class of a lentil is by seed coat color. Red lentils may be confirmed by the cotyledon color. Lentil varieties may have a wide range of seed coat colors from green, red, speckled green, black and tan. The cotyledon color may be red, yellow or green. The size and color of each Indian Lentil type (i.e. Red, Green and Yellow) is determined to be large or Medium or small, then size and color becomes part of the grade name. An Intelligent system is used to identify the type of Indian lentils from bulk samples. The samples were acquired from the proposed image acquisition system with image resolution 640x480. The proposed system facilitating kernels size and color measurement using image processing techniques. These Lentil size measurements, when combined with color attributes of the sample, classify three lentil varieties commonly grown in India with an accuracy approaching 97.08%.

Item Type: Article
Uncontrolled Keywords: Size and Color measurement, Lentil, Image Processing, Artificial Neural Network
Subjects: Engineering > MIT Manipal > Computer Science and Engineering
Depositing User: MIT Library
Date Deposited: 27 Jan 2016 10:00
Last Modified: 27 Jan 2016 10:00
URI: http://eprints.manipal.edu/id/eprint/145139

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