Journal of Electrical and Electronic Engineering
Volume 8, Issue 3, June 2020, Pages: 71-80
Received: Apr. 26, 2020;
Accepted: May 22, 2020;
Published: Jun. 20, 2020
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Rahul Kher, Department of Electronics & Communication Engg, G H Patel College of Engineering & Technology, Vallabh Vidyanagar, India
Heena Kher, Department of Electronics & Communication Engg, A D Patel Institute of Technology, New Vallabh Vidyanagar, India
Soft computing techniques have found numerous applications in various domains of image processing and computer vision. This paper represents a survey on various soft computing methods’- fuzzy logic, neural network, neuro-fuzzy systems, genetic algorithm, evolutionary computing, support vector machine etc. - applications in various image processing areas. There are numerous applications of SC ranging from industrial automation to agriculture and from medical imaging to aerospace engineering, but this paper deals with the relevance and feasibility of soft computing tools in the area of image processing, analysis and recognition. The techniques of image processing stem from two principal applications namely, improvement of pictorial information for human interpretation and processing of scene data for automatic machine perception. The different tasks involved in the process include enhancement, filtering, noise reduction, segmentation, contour extraction, skeleton extraction etc. Their ultimate aim is to make understanding, recognition and interpretation of the images from the processed information available from the image pattern. There are many hybridized approaches like neuro-fuzzy system (NFS), fuzzy-neural network (FNN), genetic-fuzzy systems, neuro-genetic systems, neuro-fuzzy-genetic system exist for various image processing applications. Tools like genetic algorithms (GAs), simulated annealing (SA), and tabu search (TS) etc. have been incorporated with soft computing tools for applications involving optimization.
Soft Computing Techniques for Various Image Processing Applications: A Survey, Journal of Electrical and Electronic Engineering. Special Issue: Soft Computing Methods for Electrical and Electronics Engineering Applications.
Vol. 8, No. 3,
2020, pp. 71-80.
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