Title: Object tracking using parallel local colour histogram method

Authors: Chandra Sekhar Panda, Pradeep Kumar Mallick, Srikanta Patnaik

Addresses: Department of Computer Science and Applications, Sambalpur University, Jyoti Vihar, Burla 768019, Orissa, India. ' Department of Computer Science, Interscience Institute of Management and Technology, Kantabada Bhubaneswar – 752054, Orissa, India. ' Department of Computer Science, Interscience Institute of Management and Technology, Kantabada Bhubaneswar – 752054, Orissa, India

Abstract: In this paper, a novel algorithm for object tracking in image sequences using local colour histogram method (LCHM) is presented. In order to represent the object to be tracked, the proposed local colour histogram model divides the image into distinct blocks of same size and encodes the colour distribution of each local block. The histogram of each local block of the query image is compared in parallel with the corresponding local block of the test image(s) and the similarity measure is computed using a metric and compared against a threshold. Histogram matching is performed by distance measures like histogram intersection, Euclidean distance and histogram quadratic distance and their performance for detecting the presence of the object in the image is compared. Experimental results show that for retrieval of visually similar object from the image sequences, the local histogram method gives good retrieval precision with speed.

Keywords: colour histograms; distance measure; histogram matching; object tracking; retrieval precision; recall; image sequences.

DOI: 10.1504/IJCVR.2010.038191

International Journal of Computational Vision and Robotics, 2010 Vol.1 No.4, pp.363 - 379

Published online: 21 Jan 2011 *

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