Abstract
In this paper, we introduce an algorithm for the fitting of bounding rectangle to a closed region 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 computes 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 the 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%.
| Original language | English |
|---|---|
| Pages (from-to) | 3442-3446 |
| Number of pages | 5 |
| Journal | International Journal of Engineering and Technology(UAE) |
| Volume | 7 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 01-01-2018 |
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All Science Journal Classification (ASJC) codes
- Biotechnology
- Computer Science (miscellaneous)
- Environmental Engineering
- Chemical Engineering(all)
- Engineering(all)
- Hardware and Architecture
Cite this
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White whole (WW) grades cashew kernel's classification using Artificial Neural Network (ANN). / Narendra, V. G.; Shetty, Dashrathraj K.
In: International Journal of Engineering and Technology(UAE), Vol. 7, No. 4, 01.01.2018, p. 3442-3446.Research output: Contribution to journal › Article
TY - JOUR
T1 - White whole (WW) grades cashew kernel's classification using Artificial Neural Network (ANN)
AU - Narendra, V. G.
AU - Shetty, Dashrathraj K.
PY - 2018/1/1
Y1 - 2018/1/1
N2 - In this paper, we introduce an algorithm for the fitting of bounding rectangle to a closed region 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 computes 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 the 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%.
AB - In this paper, we introduce an algorithm for the fitting of bounding rectangle to a closed region 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 computes 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 the 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%.
UR - http://www.scopus.com/inward/record.url?scp=85057614743&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85057614743&partnerID=8YFLogxK
U2 - 10.14419/ijet.v7i4.14878
DO - 10.14419/ijet.v7i4.14878
M3 - Article
AN - SCOPUS:85057614743
VL - 7
SP - 3442
EP - 3446
JO - International Journal of Engineering and Technology(UAE)
JF - International Journal of Engineering and Technology(UAE)
SN - 2227-524X
IS - 4
ER -