Abbas H. Hassin Alasadi

Work place: Computer Science Department, Science College, Basra University, Basra, Iraq.



Research Interests: Information Retrieval, Medical Image Computing, Image Processing, Computer systems and computational processes, Human-Computer Interaction


Abbas H. Hassin Alasadi is Assistant Professor and Postgraduate Program Coordinator of the Department of Computer Science at Basra University. He received his PhD degree from School of Engineering and Computer Science / Harbin Institute of Technology, China. He spent more than ten years as Assistant Professor at different Universities abroad the current position. His research interests include Medical Image processing, Biometrics, Information retrieval, and Human-computer interaction. His research work have been published in various international journals and conferences. Dr. Abbas is an active reviewer in many journals of the areas of computer science and software engineering. He is one of ACIT, UJCS, and IJPRAI members.

Author Articles
Effect of Reducing Colors Number on the Performance of CBIR System

By Abbas H. Hassin Alasadi Saba Abdual Wahid

DOI:, Pub. Date: 8 Sep. 2016

Taking inspiration from the fact that a human can distinguish only a limited number of colors, reducing the number of colors is an interesting task to be incorpo-rated in image retrieval systems that is based on using only the most discriminative colors, which most of the time yields better results.
Accordingly, the main goal of this paper is to study the influence on performance of reducing the colors number contained in images. Accomplishing this task poses an extra overhead on the system, which requires more com-putation time, but, on the other hand, can accelerate the comparison process. Due to their popularity and success, we specifically concentrate this study on histogram in-dexing methods, using both Euclidean distance and histo-gram intersection to assess consequently the distance and the similarity between images. Some simple, pertinent ideas related to the way we compare a pair of images using Euclidean Distance are given in the end of the pa-per, supported by preliminary obtained results. 

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