A note on the gradient of a multi-image
Computer Vision, Graphics, and Image Processing - Lectures notes in computer science, Vol. 201 (G. Goos and J. Hartmanis, Eds.)
A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge Detection with Embedded Confidence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing
Automatic edge detection using 3 × 3 ideal binary pixel patterns and fuzzy-based edge thresholding
Pattern Recognition Letters
A novel edge detection method based on the maximizing objective function
Pattern Recognition
IEEE Transactions on Image Processing
Vector order statistics operators as color edge detectors
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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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.