Abstract
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.
Highlights
Soft Computing (SC) is an important field that comprises of techniques like fuzzy logic, neural computing, evolutionary computation, machine learning and probabilistic reasoning
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
This paper presents a survey on soft computing methods’ applications in various fields of image processing and computer vision, for example image filtering/ de-noising, image segmentation, image classification, image compression, character/ text recognition, medical image analysis, object detection, extracting edges & skeletons
Summary
Soft Computing (SC) is an important field that comprises of techniques like fuzzy logic, neural computing, evolutionary computation, machine learning and probabilistic reasoning. Because of their inherent learning and cognitive ability and good tolerance of uncertainty and imprecision, the SC techniques have been applied in varieties of domains. 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. This paper presents a survey on soft computing methods’ applications in various fields of image processing and computer vision, for example image filtering/ de-noising, image segmentation, image classification, image compression, character/ text recognition, medical image analysis, object detection, extracting edges & skeletons
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