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General Information
Prof. Wael Badawy
Department of Computing and Information Systems Umm Al Qura University, Canada
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.
IJCTE 2016 Vol.8(5): 415-418 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2016.V8.1081

Horse Detection Using Haar Like Features

M. S. Uddin and A. Y. Akhi
Abstract—A commonly used approach for detecting objects is based on the techniques of “boosting” and “cascading”, which allow for real-time detection. In this paper I have developed a classifier for detecting horses from images or from real time video sources. For that purpose the Haar-like features were used to discriminate horses. Those features were used as input in a learning algorithm, based on AdaBoost, which selects a small number of critical visual features from a larger set and yields an extremely efficient classifier.

Index Terms—Horse detection, object detection, haar-like features, adaboost.

Mohammad Salah Uddin is with Dipartimento di Ingegneria Informatica Automatica e Gestionale Antonio Ruberti, Sapienza Universit`a di Roma, Rome, Italy (e-mail: uddin@dis.uniroma1.it).
Afroza Yesmin Akhi is with the Department of Computer Science and Engineering, East West University, Dhaka, Bangladesh (e-mail: ankhi.ayaz@yahoo.com).


Cite:M. S. Uddin and A. Y. Akhi, "Horse Detection Using Haar Like Features," International Journal of Computer Theory and Engineering vol. 8, no. 5, pp. 415-418, 2016.

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