Authors: Jamil Ahmad; Khan Muhammad; Zahoor Jan
Addresses: Department of Computer Science, Islamia College, Peshawar, Pakistan ' College of Electronics and Information Engineering, Sejong University, Seoul, South Korea ' Department of Computer Science, Islamia College, Peshawar, Pakistan
Abstract: Image classification and retrieval has significant importance in a wide variety of applications like object recognition, tracking, and content based retrieval, etc. Images usually consist of various objects which are segmented and then analysed for object-based classification and recognition. Owing to the absence of intensity and colour information, binary objects are difficult to recognise. They are usually represented using compact, geometrically invariant and robust features extracted from the object's contour or interior region. These features form the basis for recognition and govern the overall performance of classification systems. A new shape signature is introduced in this paper for representing shapes through angular profiles signature which are extracted from objects enclosed within minimum bounding circles. We have evaluated the discriminatory capabilities of this signature in shape recognition and retrieval on two shape datasets. Experimental results indicate that the signature is able to represent shapes effectively, achieving overall accuracy of 94%.
Keywords: angular profiles; shape signature; classification; descriptors; image classification; image retrieval; feature extraction; shape recognition; object recognition.
International Journal of Applied Pattern Recognition, 2016 Vol.3 No.3, pp.276 - 292
Received: 31 Dec 2015
Accepted: 28 Jun 2016
Published online: 13 Oct 2016 *