• Journal of Information Processing Systems
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• 제9권4호
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• pp.575-591
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• 2013

Most of the edge detection methods available in literature are gradient based, which further apply thresholding, to find the final edge map in an image. In this paper, we propose a novel method that is based on fuzzy logic for edge detection in gray images without using the gradient and thresholding. Fuzzy logic is a mathematical logic that attempts to solve problems by assigning values to an imprecise spectrum of data in order to arrive at the most accurate conclusion possible. Here, the fuzzy logic is used to conclude whether a pixel is an edge pixel or not. The proposed technique begins by fuzzifying the gray values of a pixel into two fuzzy variables, namely the black and the white. Fuzzy rules are defined to find the edge pixels in the fuzzified image. The resultant edge map may contain some extraneous edges, which are further removed from the edge map by separately examining the intermediate intensity range pixels. Finally, the edge map is improved by finding some left out edge pixels by defining a new membership function for the pixels that have their entire 8-neighbourhood pixels classified as white. We have compared our proposed method with some of the existing standard edge detector operators that are available in the literature on image processing. The quantitative analysis of the proposed method is given in terms of entropy value.

• 제어로봇시스템학회논문지
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• 제11권5호
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• pp.423-428
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• 2005

This paper proposes a new edge detection method using a $3{\times}3$ ideal binary pattern and lookup table (LUT) for the mobile robot localization without any parameter adjustments. We take the mean of the pixels within the $3{\times}3$ block as a threshold by which the pixels are divided into two groups. The edge magnitude and orientation are calculated by taking the difference of average intensities of the two groups and by searching directional code in the LUT, respectively. And also the input image is not only partitioned into multiple groups according to their intensity similarities by the histogram, but also the threshold of each group is determined by fuzzy reasoning automatically. Finally, the edges are determined through non-maximum suppression using edge confidence measure and edge linking. Applying this edge detection method to the mobile robot localization using projective invariance of the cross ratio. we demonstrate the robustness of the proposed method to the illumination changes in a corridor environment.

• 전자공학회논문지S
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• 제35S권1호
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• pp.105-113
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• 1998

A new image processor is implemented for high-speed digital copiers and facsimiles. The imgage processor performs CCD and CIS interface, pre-processing, enlargement andreduction of gray level image, and various halftoning algorithms. Implemented halftoning algorithms are simple thresholding, fuzzy based mixed mode thresholding, dithering, and edge enhanced error diffusion. The result of binarization is transferred to a printer with serial or paralel output ports. Line by line pipelined data prodessing architecture is employed with time sharing access of the external memory. In receiving mode, it converts the resolution of received binary image for compatibility with conventional facsimile. In copy mode, a line of A3 paper with 400 dpi is processed with in 2.5 ms. The prototype of image processor was implemented usig Laser Programmable Gate Array (LPGA) with 0.8.mu.m technology.