Evolutionary Cellular Automata Based-Approach for Edge Detection

Slatnia, Sihem; Batouche, Mohamed; Melkemi, Kamal Eddine

doi:10.1007/978-3-540-73400-0_51

Cited by 28 publications

(6 citation statements)

References 7 publications

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“…In this broad area of research that we analyze, we must work with the inverse problem where we seek the optimal rules that gives the best detection of convex hulls in different formats outline objects in the image. In order to explore all configurations in the space research, we grouped the rules in packets [12]. CA can be interpreted like a set of rules which through an EvCA, we can find one or several appropriate rules for a definite problem of polygonal or curved convex hull.…”

Section: The Evca For Convex Hull Detectionmentioning

confidence: 99%

Evolutionary Cellular Automata Based-Approach for Convex Hull Detection

2015

IJCCIE

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Abstract-Predicting the behavior of complex systems before their spreading, will be of fundamental importance in the near future. In this context, this paper present the use of an evolutionary process to seek a specialized powerful packet of Cellular Automata among a set of best transitions rules for extracting convex hull in a given black-white image of a polygonal and curved edge. This best set of local rules determines the future state of cellular automata in an asynchronous way. The Genetic Algorithm is applied to search the best cellular automata rules that can realize better the convex hull detection.

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Section: The Evca For Convex Hull Detectionmentioning

confidence: 99%

Evolutionary Cellular Automata Based-Approach for Convex Hull Detection

2015

IJCCIE

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“…There are still papers attempting to solve the trivial task of binary image boundary detection using genetic algorithms and CA [Batouche et al (2006); Slatnia et al (2007)]. Another example at the same level attempts (with limited success) to generate simple shapes such as a square, circle, etc., again using genetic algorithms [Chavoya and Duthen (2006)].…”

Section: Genetic Algorithmsmentioning

confidence: 99%

Cellular Automata as a Tool for Image Processing

Rosin

Sun

2011

Emerging Topics in Computer Vision and Its Applications

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An overview is given on the use of cellular automata for image processing. We first consider the number of patterns that can exist in a neighbourhood, allowing for invariance to certain transformation. These patterns correspond to possible rules, and several schemes are described for automatically learning an appropriate rule set from training data. Two alternative schemes are given for coping with gray level (rather than binary) images without incurring a huge explosion in the number of possible rules. Finally, examples are provided of training various types of cellular automata with various rule identification schemes to perform several image processing tasks.

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“…In literature one can find several examples of CAs applications in image processing [6,8] as well as evolving by a genetic algorithm CAs rules in image processing task [9]. Some of them deal with image enhancement, detection of edges, noise reduction, image compression, etc.…”

Section: Introductionmentioning

confidence: 99%

Discovery by Genetic Algorithm of Cellular Automata Rules for Pattern Reconstruction Task

Piwonska

Seredyński

2010

Lecture Notes in Computer Science

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Abstract. This paper presents results of the study on application of two-dimensional, three-state cellular automata with von Neumann neighborhood to perform pattern reconstruction task. Searching efficient cellular automata rules is conducted with use of a genetic algorithm. Experiments show a very good performance of discovered rules in solving the reconstruction task despite minimum radius of neighborhood and only partial knowledge about neighborhood states available. The paper also presents interesting reusability possibilities of discovered rules in reconstructing patterns different but similar to ones used during artificial evolution.

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Evolutionary Cellular Automata Based-Approach for Edge Detection

Cited by 28 publications

References 7 publications

Evolutionary Cellular Automata Based-Approach for Convex Hull Detection

Evolutionary Cellular Automata Based-Approach for Convex Hull Detection

Cellular Automata as a Tool for Image Processing

Discovery by Genetic Algorithm of Cellular Automata Rules for Pattern Reconstruction Task

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