Muzzle classification using neural networks
Joint Authors
al-Bakri, Hazim
al-Haddad, Hajir
al-Hinnawi, Ibrahim M.
Source
The International Arab Journal of Information Technology
Issue
Vol. 14, Issue 4 (31 Jul. 2017), pp.464-472, 9 p.
Publisher
Publication Date
2017-07-31
Country of Publication
Jordan
No. of Pages
9
Main Subjects
Abstract EN
There are multiple techniques used in image classification such as Support Vector Machines (SVM), Artificial Neural Networks (ANN), Genetic Algorithms (GA), Fuzzy measures, and Fuzzy Support Vector Machines (FSVM).
Classification of muzzle depending on one of this artificial technique has become widely known for guaranteeing the safety of cattle products and assisting in veterinary disease supervision and control.
The aim of this paper is to focus on using neural network technique for image classification.
First the area of interest in the captured image of muzzle is detected then pre-processing operations such as histogram equalization and morphological filtering have been used for increasing the contrast and removing noise of the image.
Then, using box-counting algorithm to extract the texture feature of each muzzle.
This feature is used for learning and testing stage of the neural network for muzzle classification.
The experimental result shows that after 15 input cases for each image in neural training step, the testing result is true and gives us the correct muzzle detection.
Therefore, neural networks can be applied in classification of bovines for breeding and marketing systems registration.
American Psychological Association (APA)
al-Hinnawi, Ibrahim M.& al-Bakri, Hazim& al-Haddad, Hajir. 2017. Muzzle classification using neural networks. The International Arab Journal of Information Technology،Vol. 14, no. 4, pp.464-472.
https://search.emarefa.net/detail/BIM-902707
Modern Language Association (MLA)
al-Hinnawi, Ibrahim M.…[et al.]. Muzzle classification using neural networks. The International Arab Journal of Information Technology Vol. 14, no. 4 (Jul. 2017), pp.464-472.
https://search.emarefa.net/detail/BIM-902707
American Medical Association (AMA)
al-Hinnawi, Ibrahim M.& al-Bakri, Hazim& al-Haddad, Hajir. Muzzle classification using neural networks. The International Arab Journal of Information Technology. 2017. Vol. 14, no. 4, pp.464-472.
https://search.emarefa.net/detail/BIM-902707
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 471-472
Record ID
BIM-902707