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• W69161259 abstract "This paper proposes a novel edge detection method for both gray level images and color images, and which can overcome the limitations of gradient-based edge detection methods. A vector distance between feature vector and minimum vector which determines the edge intensity is defined based on four directional summed magnitude differences in a mask, and partial normalization is applied to facilitate threshold selecting. This paper also proposes an improved approach to determine the edge direction. According to the improved edge direction, non-maxima suppression is applied to thin edges, and final edges are extracted automatically using OTSU, even in a changing environment. Extensive experimental results have demonstrated that the proposed method does well in keeping low-contrast edges, selecting threshold and processing time." @default.
• W69161259 created "2016-06-24" @default.
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• W69161259 date "2011-09-01" @default.
• W69161259 modified "2023-09-23" @default.
• W69161259 title "Automatic edge detection using vector distance and partial normalization" @default.
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