Fuzzy image processing is a powerful tool formulation of expert knowledge edge and the combination of imprecise information from different sources. The fuzzy technique is an operator in order to simulate at a mathematical level the compensatory behavior in process of decision making or subjective evaluation. Edge is a basic feature of image. The image edges include rich information that is very...

In this paper, a new algorithm for edge detection based on fuzzyconcept is suggested. The proposed approach defines dynamic membershipfunctions for different groups of pixels in a 3 by 3 neighborhood of the centralpixel. Then, fuzzy distance and -cut theory are applied to detect the edgemap by following a simple heuristic thresholding rule to produce a thin edgeimage. A large number of experime...

In this research paper, we present a novel frame work for handling $m$-polar information by combining the theory of $m-$polar fuzzy  sets with graphs. We introduce certain types of edge regular $m-$polar fuzzy graphs and edge irregular $m-$polar fuzzy graphs. We describe some useful properties of edge regular, strongly edge irregular and strongly edge totally irregular $m-$polar fuzzy graphs. W...

This research work proposed an improved edge detection techniques using fuzzy sets. The problem is to find edges in the image, as a first step in the process of scene reconstruction. Edges are scale-dependent and an edge may comprise other edges, but at a definite scale, an edge still has no width. This paper has presented different edge detection operators and their benefit when they merge wit...

In recent years due to improvements of technology within automobile industry, design process of advanced driver assistance systems for collision avoidance and traffic management has been investigated in both academics and industrial levels. Detection of traffic signs is an effective method to reach the mentioned aims. In this paper a new intelligent driver assistance system based on traffic...

In this paper, the local fuzzy fractal dimension (LFFD) is proposed to represent the feature of local image complexity. The definition of LFFD is an extension of the box-counting dimension of discrete sets by incorporating the fuzzy set. The relationship between LFFD and local intensity changing is investigated by experiments, which proves that LFFD is an important feature of edges and is insen...

Soft Computing is an emerging field that consists of complementary elements of fuzzy logic, neural computing and evolutionary computation. Soft computing techniques have found wide applications. One of the most important applications is edge detection for image segmentation. The process of partitioning a digital image into multiple regions or sets of pixels is called image segmentation. Edge is...

Image segmentation is one of the most important and challenging problems in image processing. The main purpose of image segmentation is to partition an image into a set of disjoint regions with uniform attributes. In this study, we propose an improved method for edge detection and image segmentation using fuzzy cellular automata. In the first stage, we introduce a new edge detection method base...