Region-based segmentation of Hexagonal digital images using membrane computing

Isawasan, Pradeep; Venkat, Ibrahim; Subramanian, K. G.; Khader, Ahamad Tajudin; Osman, Omar; Christinal, Hepzibah A.

doi:10.1109/acmc.2014.7065806

Cited by 6 publications

(9 citation statements)

References 10 publications

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“…As can be depicted from the literature review presented above, only one work has implemented the region-based segmentation in 6-adjacency of hexagonal image (Isawasan, et al, 2014). However, Isawasan, et al, did not clearly illustrate how their approach has been implemented in P-Lingua programming language.…”

Section: Related Workmentioning

confidence: 99%

“…As can be depicted from the literature review presented previously, only one work has implemented the segmentation of hexagonal (6-adjacent) image (Isawasan, et al, 2014). The majority of the work reviewed was implemented using 4-adjacent.…”

Section: )mentioning

confidence: 99%

“…Peng, et al (2014) have proposed a novel segmentation by improving the traditional region-based colour image segmentation method using tissue-like P systems. Isawasan, et al (2014) used tissue-like P system rules to perform region-based segmentation of 2D hexagonal images where the segmentation steps has been done in 7 steps, but they did not illustrate how they used P-Lingua to perform the segmentation. Peng, et al (2015) have proposed a new method using cell-like P system to solve the optimal multi-level thresholding problem.…”

Section: Related Workmentioning

confidence: 99%

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

Yahya

Shamsuddin

Hasan

et al. 2016

ARO

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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 segmentations 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 little number of steps.Index Terms-Membrane computing, edge-based image segmentation, P-Lingua, region-based image segmentation, Tissue-like P system.

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Section: Related Workmentioning

confidence: 99%

Section: )mentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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

Yahya

Shamsuddin

Hasan

et al. 2016

ARO

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“…Furthermore, proposed a novel segmentation by adaptive traditional region-based color segmentation method using tissue-like P system (membrane algorithm). Isawasan, et al (2014) developed a tissue-like P system using MC rules to segment hexagonal images, wherein the segmentation has been done in 7 steps. proposed a novel method using cell-like P system (membrane algorithm) to solve the optimal multilevel thresholding problem.…”

Section: Related Workmentioning

confidence: 99%

Three-dimensional Image Segmentation using Tissue-like P System

Yahya¹,

Yahya

Alsalibi

et al. 2017

ARO

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Abstract-Membrane computing (MC), which abstracts computational models from the structure and functioning of biological cells or population of cells in tissues, has served as a rich framework for handling many problems. Various types of P systems have been proposed in the literature to perform edge-based and region-based segmentation of two-dimensional digital images. However, less attention has been paid to the segmentation of threedimensional (3D) medical images. Hence, the main contribution of this paper is to propose a tissue-like P system for segmenting 3D medical images. To the best of our knowledge, this is the first work that practically adapts MC for 3D images. Experimental results demonstrate the efficiency of the proposed approach in segmenting 3D images, and it has the potential to be used in realworld applications.Index Terms-Membrane computing, Region-based image segmentation, Three-dimensional images, Tissue-like P systems.

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“…The models of P system are mainly divided into three types, namely, the cell-like P system [2], the tissue-like P system [3] and the neural-like P system [4]. They have been applied to solve the problems such as NP problems [5]- [8], image processing [9], [10], arithmetic operations [11]- [14] and so on.…”

Section: Introductionmentioning

confidence: 99%

The P System Design Method based on the P Module

Guo¹,

Peng²,

Lian³

2018

ijacsa

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Abstract-Membrane computing is a kind of biocomputing model. At present, the main research areas of membrane computing are computational models and P system design. With the expansion of the P system scale, how to rapidly construct the P system has become a prominent issue. Designing P system based on P module is a P system design method proposed in recent years. This method provides information hiding and can build P system through recursive combination. However, the current P module design lacks a unified design method and lacks the standard process of building P system from P module. This paper studies the structural characteristics of cell-like P systems, and proposes an improved P module design method and a process for assembling P systems through P modules. In order to fully expound the design method of P module, the P system for the square root of the large number was analyzed and designed. And the correctness of the P system based on the P module design method was verified by an instance.

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Region-based segmentation of Hexagonal digital images using membrane computing

Cited by 6 publications

References 10 publications

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

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

Three-dimensional Image Segmentation using Tissue-like P System

The P System Design Method based on the P Module

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