Computer Vision System to Estimate cashew kernel (White wholes) grade Geometric and Color parameters

Narendra , V G and Hareesha , K S (2014) Computer Vision System to Estimate cashew kernel (White wholes) grade Geometric and Color parameters. Electronic Journal of Polish Agricultural Universities, 17 (4). pp. 1-28. ISSN 1505-0297

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Abstract

The geometric parameters along with related colour properties of food and agricultural products are important in order to characterize and describe its quality. Presently, the quality assessment of food and agricultural products on the basis of visual inspection are done by human, so it is time consuming and laborious. The alternative of visual inspection is computer vision system, with the application of image processing technique for this purpose can certainly reduce the human drudgery while guaranteeing the quality of food and agricultural products. In this paper, a new colour and geometric parameters estimation methods suggested, to provide automatic and intuitive way of quality inspection of cashew kernel from an image accurately. The geometric parameters are obtained manually and proposed method, and we have estimated the average values (i.e. minimum and maximum) of length, width and an area of cashew kernels (white wholes) grade. Finally, compared the results of geometric parameters using proposed method and manually done. To identify the representation of colour values in suitable colour space for cashew kernel, we have investigated the hardware-oriented (i.e. RGB color space), human-oriented (i.e. HSV color space) and instrumental (i.e. CIEL*A*B* color space). It is estimated from our research that, the statistical measurements of cashew kernels (white wholes) grade colour parameters from the proposed methods. Finally the paper concludes by highlighting the necessity of such computer vision system and insight into the methodology that attempts to fix the universal estimation of colour and geometric parameters measurement of cashew kernels (white wholes) grade.

Item Type: Article
Uncontrolled Keywords: Quality, Geometric and colour parameters,Cashew Kernels,Computer Vision
Subjects: Engineering > MIT Manipal > Computer Science and Engineering
Engineering > MIT Manipal > MCA
Depositing User: MIT Library
Date Deposited: 15 May 2015 10:34
Last Modified: 15 May 2015 10:34
URI: http://eprints.manipal.edu/id/eprint/142648

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