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JOIG 2024 Vol.12(4):410-416
doi: 10.18178/joig.12.4.410-416

A Novel Color Feature for the Improvement of Pigment Spot Extraction in Iris Images

Mohamad Faizal Ab Jabal 1,*, Asniyani Nur Haidar Abdullah 2, 4, Fallah H. Najjar 3, 4, Suhardi Hamid 5, Ahmad Khudzairi Khalid 1, and Wan Dorishah Wan Abdul Manan6
1. School of Computing Sciences, College of Computing, Informatics and Mathematics, Universiti Teknologi MARA Johor Branch Pasir Gudang Campus, Masai, Johor, Malaysia
2. Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka Hang Tuah Jaya, Durian Tunggal, Melaka, Malaysia
3. Department of Computer Systems Techniques, Technical Institute of Najaf, Al-Furat Al-Awsat Technical University, Najaf, Iraq
4. Department of Emergent Computing, Faculty of Computing, Universiti Teknologi Malaysia, Johor Bahru, Malaysia
5. School of Computing Sciences, College of Computing, Informatics and Mathematics, Universiti Teknologi MARA Kedah Branch, Merbok, Kedah, Malaysia
6. School of Computing Sciences, College of Computing, Informatics and Mathematics, Universiti Teknologi MARA Terengganu Branch Kuala Terengganu Campus, Kuala Terengganu, Terengganu, Malaysia
Email: m.faizal@uitm.edu.my (M.F.A.J.); asniyani@utem.edu.my (A.N.H.A.); fallahnajjar@atu.edu.iq (F.H.N.); suhardi@uitm.edu.my (S.H.); ahmad4829@uitm.edu.my (A.K.K.); wand@uitm.edu.my (W.D.W.A.M.)
*Corresponding author

Manuscript received February 27, 2024; revised June 12, 2024; accepted July 2, 2024; published November 25, 2024.

Abstract—Feature extraction plays a vital role in the segmentation of regions of interest in medical images. While histograms offer a reliable method for analyzing color properties, the challenge of defining the pigment spot color has motivated the search for a practical feature for extraction. Consequently, analyzing the image using histograms and the HSV (Hue, Saturation, Value) color space led to the groundbreaking discovery of a reliable color feature and an exciting opportunity for pigment spot extraction. This study utilized 131 pigment spot images from the Miles Research datasets. The Region of Interest (ROI) was determined using a histogram color-based saturation intensity component, revealing new findings of thresholds ranging from 0.70 to 0.90. The results indicate that the proposed method achieved a Detection Rate (DR) of 37.1% (49 images), a False Acceptance Rate (FAR) of 14.5% (19 images), and a False Rejection Rate (FRR) of 48.4% (63 images). While the detection rate shows room for improvement, the proposed method significantly reduces the FAR to 14.5%, compared to 64.8% and 65.3% in color-based segmentation and simple color detection, respectively. This newfound feature contributes to improved accuracy and efficiency in medical image analysis, facilitating better patient diagnosis and treatment planning.

Keywords—color feature, feature extraction, pigment spot, histogram, iris image

Cite: Mohamad Faizal Ab Jabal, Asniyani Nur Haidar Abdullah, Fallah H. Najjar, Suhardi Hamid, Ahmad Khudzairi Khalid, and Wan Dorishah Wan Abdul Manan, "A Novel Color Feature for the Improvement of Pigment Spot Extraction in Iris Images," Journal of Image and Graphics, Vol. 12, No. 4, pp. 410-416, 2024.

Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.

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