Cover Image

Binary classification using SVM for sick and healthy chicken based on chicken’s excrement image

The purpose of this paper is to classify between healthy and sick chicken based on their dropping. Most chicken farm management system in Malaysia is highly dependent on human surveillance method. This method, however, does not focus on early disease detection hence, unable to and alert chicken farm...

Full description

Saved in:
Bibliographic Details
Main Authors: Aziz, N. A., Othman, M. F.
Format: Article
Published: Universiti Putra Malaysia Press 2017
Subjects:
T Technology (General)
Online Access:http://eprints.utm.my/id/eprint/77021/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029641655&partnerID=40&md5=9de023a298899fcbb257adb855475c4a
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.77021
record_format eprints
spelling my.utm.770212018-05-31T09:34:43Z http://eprints.utm.my/id/eprint/77021/ Binary classification using SVM for sick and healthy chicken based on chicken’s excrement image Aziz, N. A. Othman, M. F. T Technology (General) The purpose of this paper is to classify between healthy and sick chicken based on their dropping. Most chicken farm management system in Malaysia is highly dependent on human surveillance method. This method, however, does not focus on early disease detection hence, unable to and alert chicken farmers to take necessary action.. Therefore, the need to improve the biosecurity of chicken poultry production is essential to prevent infectious disease such as avian influenza. The classification of sick and healthy chicken based solely on chicken’s excrement using the support vector machine is proposed. First, the texture is examined using grey-level co-occurrence matrix (GLCM) approach. A GLCM based texture feature set is derived and used as input for the SVM classifier. Comparison are made using more and then less extracted features, less extracted features and also applying Gabor filter to these features to see the effect it has on classification accuracy. Results show that having more features extracted using GLCM techniques allows for greater classification accuracy. Universiti Putra Malaysia Press 2017 Article PeerReviewed Aziz, N. A. and Othman, M. F. (2017) Binary classification using SVM for sick and healthy chicken based on chicken’s excrement image. Pertanika Journal of Science and Technology, 25 (S). pp. 315-324. ISSN 0128-7680 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029641655&partnerID=40&md5=9de023a298899fcbb257adb855475c4a
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic T Technology (General)
spellingShingle T Technology (General)
Aziz, N. A.
Othman, M. F.
Binary classification using SVM for sick and healthy chicken based on chicken’s excrement image
description The purpose of this paper is to classify between healthy and sick chicken based on their dropping. Most chicken farm management system in Malaysia is highly dependent on human surveillance method. This method, however, does not focus on early disease detection hence, unable to and alert chicken farmers to take necessary action.. Therefore, the need to improve the biosecurity of chicken poultry production is essential to prevent infectious disease such as avian influenza. The classification of sick and healthy chicken based solely on chicken’s excrement using the support vector machine is proposed. First, the texture is examined using grey-level co-occurrence matrix (GLCM) approach. A GLCM based texture feature set is derived and used as input for the SVM classifier. Comparison are made using more and then less extracted features, less extracted features and also applying Gabor filter to these features to see the effect it has on classification accuracy. Results show that having more features extracted using GLCM techniques allows for greater classification accuracy.
format Article
author Aziz, N. A.
Othman, M. F.
author_facet Aziz, N. A.
Othman, M. F.
author_sort Aziz, N. A.
title Binary classification using SVM for sick and healthy chicken based on chicken’s excrement image
title_short Binary classification using SVM for sick and healthy chicken based on chicken’s excrement image
title_full Binary classification using SVM for sick and healthy chicken based on chicken’s excrement image
title_fullStr Binary classification using SVM for sick and healthy chicken based on chicken’s excrement image
title_full_unstemmed Binary classification using SVM for sick and healthy chicken based on chicken’s excrement image
title_sort binary classification using svm for sick and healthy chicken based on chicken’s excrement image
publisher Universiti Putra Malaysia Press
publishDate 2017
url http://eprints.utm.my/id/eprint/77021/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029641655&partnerID=40&md5=9de023a298899fcbb257adb855475c4a
_version_ 1643657475362127872
score 13.211869

Similar Items