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DOI: 10.14569/IJACSA.2020.0110730
PDF

Object Detection using Template and HOG Feature Matching

Author 1: Marjia Sultana
Author 2: Tasniya Ahmed
Author 3: Partha Chakraborty
Author 4: Mahmuda Khatun
Author 5: Md. Rakib Hasan
Author 6: Mohammad Shorif Uddin

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 7, 2020.

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Abstract: In the present era, the applications of computer vision is increasing day by day. Computer vision is related to the automatic recognition, exploration and extraction of the necessary information from a particular image or a group of image sets. This paper addresses the method to detect the desired object from an image. Usually, a template of the desired object is used in detection through a matching technique named Template Matching. But it works well when the template image is cropped from the original one, which is not always invariant due to various transformations in the test images. To cope with this difficulty and to develop a generalized approach, we investigate in detail another technique which is known as HOG (Histogram of Oriented Gradient) approach. In HOG, the image is divided into overlapping blocks of template size and then compare each block’s normalized HOG with the normalized HOG of the template to find the best match of the object. We perform experiments with a large number of images and have found satisfactory performance.

Keywords: Computer vision; template matching; HOG; feature extraction

Marjia Sultana, Tasniya Ahmed, Partha Chakraborty, Mahmuda Khatun, Md. Rakib Hasan and Mohammad Shorif Uddin, “Object Detection using Template and HOG Feature Matching” International Journal of Advanced Computer Science and Applications(IJACSA), 11(7), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110730

@article{Sultana2020,
title = {Object Detection using Template and HOG Feature Matching},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110730},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110730},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {7},
author = {Marjia Sultana and Tasniya Ahmed and Partha Chakraborty and Mahmuda Khatun and Md. Rakib Hasan and Mohammad Shorif Uddin}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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