Narendra , V G and Hareesha , K S (2014) Intelligent Cashew Kernels classification model using shape features. In: International Conference on Computer Science and Information Technology (ICCSIT’2014) Proceedings, Feb. 19th to 20th , Kuala Lumpur Malaysia .
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Abstract
In this paper, we introduce an algorithm for fitting of bounding rectangle to a closed regions of cashew kernel in a given image. We propose an algorithm to automatically compute the coordinates of the vertices closed form solution. Which is based on coordinate geometry and uses the boundary points of regions. The algorithm also compute directions of major and minor axis using least-square approach to compute the orientation of the given cashew kernel. More promising results were obtained by extracting shape features of a cashew kernel, it is proved that, these features may predominantly use to make better distinction of cashew kernels of different grades. The intelligent model was designed using Artificial Neural Network (ANN). The model was trained and tested using Back-Propagation learning algorithm and obtained classification accuracy of 89.74%.
Item Type: | Conference or Workshop Item (Paper) |
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Uncontrolled Keywords: | Cashew Kernel, Bounding rectangle, Shape features |
Subjects: | Engineering > MIT Manipal > Computer Science and Engineering |
Depositing User: | MIT Library |
Date Deposited: | 25 Feb 2014 06:33 |
Last Modified: | 25 Feb 2014 06:33 |
URI: | http://eprints.manipal.edu/id/eprint/138946 |
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