Tissue-like P system for Segmentation of 2D Hexagonal Images

  • Rafaa I. Yahya UTM Big Data Center, Ibnu Sina Institute for Scientific and Industrial Research. Universiti Teknologi Malaysia. http://orcid.org/0000-0003-0375-4556
  • Siti Mariyam Shamsuddin UTM Big Data Center, Ibnu Sina Institute for Scientific and Industrial Research. Universiti Teknologi Malaysia. http://orcid.org/0000-0002-0982-5629
  • Shafaatunnur Hasan UTM Big Data Center, Ibnu Sina Institute for Scientific and Industrial Research. Universiti Teknologi Malaysia.
  • Salah I. Yahya 1- UTM Big Data Center, Ibnu Sina Institute for Scientific and Industrial Research. Universiti Teknologi Malaysia. 2- Koya University http://orcid.org/0000-0002-2724-5118
DOI: https://doi.org/10.14500/aro.10135
Keywords: Membrane computing, edge-based image segmentation, P-Lingua, region-based image segmentation, Tissue-like P system

Abstract

Membrane computing, which is a new computational model inspired by the structure and functioning of biological cells and by the way the cells are organized in tissues. MC has been adopted in many real world applications including image segmentation. In contrast to the traditional square grid for representing and sampling digital images, hexagonal grid is an alternative efficient mechanism which can better represents and visualizes the curved objects. In this paper, a tissue-like P system with region-based and edge-based segmentation is used to segment two dimensional hexagonal images, wherein P-Lingua programming language is used to implement and validate the proposed system. The achieved experimental results clearly demonstrated the effectiveness of using hexagonal connectivity to segment two dimensional images in a less number of rules and computational steps. Moreover, the results reveal that this approach has the potential of segmenting large images in few number of steps.

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Author Biographies

Rafaa I. Yahya, UTM Big Data Center, Ibnu Sina Institute for Scientific and Industrial Research. Universiti Teknologi Malaysia.
Rafaa I. Yahya received her B.Sc. degree in Computer Science from Al-Rafidain University College in Baghdad, Iraq, and her M.Sc. in computer science (image processing) from the University of Al–Mustansiriyah in Baghdad, Iraq.  Currently, she is working toward her Ph.D. degree in computer science (Bioinformatics) from Universiti Teknologi Malaysia, Johor, Malaysia. Her research interests include bioinformatics, membrane computing, and image processing. 
Siti Mariyam Shamsuddin, UTM Big Data Center, Ibnu Sina Institute for Scientific and Industrial Research. Universiti Teknologi Malaysia.
Siti Mariyam Shamsuddin received her B.Sc. and M.Sc. degrees in mathematics from New Jersey and her Ph.D. degree in pattern recognition and artificial intelligence from Universiti Putra Malaysia, Malaysia. Currently, she is the Director of the UTM Big Data Center and a full professor of computer science at Universiti Teknologi Malaysia, Johor, Malaysia. Her research interests include big data analytics, machine learning, GPU computing, soft computing and its applications, pattern recognition, and geometric modelling.
Shafaatunnur Hasan, UTM Big Data Center, Ibnu Sina Institute for Scientific and Industrial Research. Universiti Teknologi Malaysia.
Shafaatunnur Hasan received her B.Sc. degree in computer science (artificial intelligence) from Universiti Malaya, her M.Sc. degree in computer science (machine learning) from Universiti Teknologi Malaysia, and her Ph.D. degree in GPU-based machine learning from Universiti Teknologi Malaysia. She is actively conducting research on multi-strategy machine learning algorithms for Big Data using GPU and bridging GPU platforms with Hadoop technology. Currently, she is the principal researcher in GPU computing for machine learning at the UTM Big Data Centre and a senior lecturer in the Faculty of Computing Universiti Teknologi Malaysia.
Salah I. Yahya, 1- UTM Big Data Center, Ibnu Sina Institute for Scientific and Industrial Research. Universiti Teknologi Malaysia. 2- Koya University
Salah I. Yahya is an Associate Professor, joined the department of Software Engineering at Koya University in 2010. He has a B.Sc. degree in Electrical Engineering, M.Sc. degree in Electronics and Communication Engineering and Ph.D. degree in Communication and Microwave Engineering. He is a Consultant at the Iraqi Engineering Union. Dr. Yahya has many scientific publications; (2) books [1] and [2], (12) Journal Articles and more than (31) conference papers. He is a senior member of the IEEE-USA and a member of AMTA-USA, SDIWC-Hong Kong. Dr. Yahya is a regular reviewer of the Electromagnetics Academy, Cambridge, USA, PIERS Journalspublications, since 2009, Science and Engineering of Composite Materials journal and International Journal of Applied Electromagnetics and Mechanics, as well as, a regular reviewer of SDIWC conferences. His h-index is (6).

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ARO Journal: Volume 4, No. 1 (2016)
Published
2016-05-18
How to Cite
Yahya, R. I., Shamsuddin, S. M., Hasan, S. and Yahya, S. I. (2016) “Tissue-like P system for Segmentation of 2D Hexagonal Images”, ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY, 4(1), pp. 35-42. doi: 10.14500/aro.10135.
Issue
Vol. 4 No. 1 (2016): Issue Six
Section
Articles

Copyright (c) 2016 Rafaa I. Yahya, Siti Mariyam Shamsuddin, Shafaatunnur Hasan, Salah Yahya

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