White whole (WW) grades cashew kernel's classification using Artificial Neural Network (ANN)

V. G. Narendra, Dashrathraj K. Shetty

Research output: Contribution to journalArticle

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 languageEnglish
Pages (from-to)3442-3446
Number of pages5
JournalInternational Journal of Engineering and Technology(UAE)
Volume7
Issue number4
DOIs
Publication statusPublished - 01-01-2018

Fingerprint

Anacardium
Neural networks
Backpropagation
Learning algorithms
Least-Squares Analysis
Geometry
Learning

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Computer Science (miscellaneous)
  • Environmental Engineering
  • Chemical Engineering(all)
  • Engineering(all)
  • Hardware and Architecture

Cite this

@article{1f48160b402947dcab6420a976a28740,
title = "White whole (WW) grades cashew kernel's classification using Artificial Neural Network (ANN)",
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{\%}.",
author = "Narendra, {V. G.} and Shetty, {Dashrathraj K.}",
year = "2018",
month = "1",
day = "1",
doi = "10.14419/ijet.v7i4.14878",
language = "English",
volume = "7",
pages = "3442--3446",
journal = "International Journal of Engineering and Technology(UAE)",
issn = "2227-524X",
publisher = "Science Publishing Corporation Inc",
number = "4",

}

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 journalArticle

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 -