Fuzzy morphology for edge detection and segmentation

Authors:
Atif Bin Mansoor;Ajmal S. Mian;Adil Khan;Shoab A. Khan
Affiliations:
National University of Science and Technology, Rawalpindi, Pakistan;National University of Science and Technology, Rawalpindi, Pakistan;National University of Science and Technology, Rawalpindi, Pakistan;National University of Science and Technology, Rawalpindi, Pakistan
Venue:
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Year:
2007

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Abstract

This paper proposes a new approach for structure based separation of image objects using fuzzy morphology. With set operators in fuzzy context, we apply an adaptive alpha-cut morphological processing for edge detection, image enhancement and segmentation. A Top-hat transform is first applied to the input image and the resulting image is thresholded to a binary form. The image is then thinned using hit-or-miss transform. Finally, m-connectivity is used to keep the desired number of connected pixels. The output image is overlayed on the original for enhanced boundaries. Experiments were performed using real images of aerial views, sign boards and biological objects. A comparison to other edge enhancement techniques like unsharp masking, sobel and laplacian filtering shows improved performance by the proposed technique.