A novel edge detection and pattern recognition algorithm based on beamlet theory for a vision-based wheeled mobile robot

Soumya, S.; Geethapriya, V.; Bharathi, S. Shankar

doi:10.1109/iccsp.2014.6950041

Cited by 2 publications

(2 citation statements)

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“…The paper presented by Bhanu and Lee tells about the expanded and comprehensive work on GAs for image segmentation. [15,16]The potential of GA is so high that it can handle very large and complex search spaces in the positions where very small amount of facts\information is present about the objective function which makes the use of GA more popular among others [6]. The paper presented by Ganesan P(2017) gives the idea of fuzzy logic-based methods which are practiced on user aligned satellite images.…”

Section: Related Workmentioning

confidence: 99%

“…A. Genetic Algorithm Holland J. in 1975 gives the idea ofGenetic algorithm which isworked on the theory of evolution [5].Population is the method of genetic algorithm [6]. In the search space each particle is giving a solution in the population which is encoded as chromosome and the algorithm will repeat the step to calculate the fitness of each particle and choose the particle with good result as the parents of next generation,now the two process which are known as crossover andmutation are performed to reproduce the next generation.…”

Section: Different Soft Computing Techniquesmentioning

confidence: 99%

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Edge Detection of Different Images using Soft Computing Techniques

Dagar¹,

Dahiya²

2019

IJRTE

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The technique by which an image or photograph is divided into several number of parts in order to analyze the segmented components such as colors, textures grey scale and edges/boundaries of the entities which are present in the image is called as image segmentations. Images obtained by segmentation methods are more understandable as compared to the original images. In the digital snap shot segmentation is essentially used to detect object boundaries present in the image. The paper presents the comparative analysis of image segmentation using soft computing methods.In this paper, we included genetic algorithm, ant colony algorithm, neural network, neuro-fuzzy genetic and adaptive neuro-fuzzy inference system. The techniques are tested on six standard test images. The peak signal to noise ratio (PSNR)is calculated for GA and ACO techniques. The results which are obtained by the above techniques prove that the value of PSNR for GA is much more as compared to the ACO technique

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Section: Related Workmentioning

confidence: 99%

Section: Different Soft Computing Techniquesmentioning

confidence: 99%