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Intelligent Image Classification-Based on Spatial Weighted Histograms of Concentric Circles

Bushra Zafar¹, Rehan Ashraf¹, Nouman Ali², Mudassar Ahmed¹, Sohail Jabbar¹, Kashif Naseer³, Awais Ahmad⁴ and Gwanggil Jeon^{5, 6}

1. Department of Computer Science, National Textile University
   Faisalabad, Pakistan
   bkgcuf@gmail.com, {rehan,mudassar}@ntu.edu.pk, sjabbar.research@gmail.com
2. Software Engineering Department, Mirpur University of Science & Technology
   Mirpur, Pakistan
   nouman.se@must.edu.pk
3. Department of Computer Engineering, Bahria University
   Islamabad, Pakistan
   kashifnaseer85@yahoo.com
4. Department of Computer Science, Bahria University
   Islamabad, Pakistan
   aahmad.marwat@gmail.com
5. School of Electronic Engineering, Xidian University
   China
6. Department of Embedded Systems Engineering, Incheon National University
   Korea
   ggjeon@gmail.com

Abstract

As digital images play a vital role in multimedia content, the automatic classification of images is an open research problem. The Bag of Visual Words (BoVW) model is used for image classification, retrieval and object recognition problems. In the BoVW model, a histogram of visual words is computed without considering the spatial layout of the 2-D image space. The performance of BoVW suffers due to a lack of information about spatial details of an image. Spatial Pyramid Matching (SPM) is a popular technique that computes the spatial layout of the 2-D image space. However, SPM is not rotation-invariant and does not allow a change in pose and view point, and it represents the image in a very high dimensional space. In this paper, the spatial contents of an image are added and the rotations are dealt with efficiently, as compared to approaches that incorporate spatial contents. The spatial information is added by constructing the histogram of circles, while rotations are dealt with by using concentric circles. A weighed scheme is applied to represent the image in the form of a histogram of visual words. Extensive evaluation of benchmark datasets and the comparison with recent classification models demonstrate the effectiveness of the proposed approach. The proposed representation outperforms the state-of-the-art methods in terms of classification accuracy.

Key words

Image Classification, Bag of Visual Words, Support Vector Machine, Weighted Histograms of Concentric Circles

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS180105025Z

Publication information

Volume 15, Issue 3 (October 2018)
Year of Publication: 2018
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Zafar, B., Ashraf, R., Ali, N., Ahmed, M., Jabbar, S., Naseer, K., Ahmad, A., Jeon, G.: Intelligent Image Classification-Based on Spatial Weighted Histograms of Concentric Circles. Computer Science and Information Systems, Vol. 15, No. 3, 615–633. (2018), https://doi.org/10.2298/CSIS180105025Z