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 Jeon5, 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