A skeleton algorithm on clusters for image edge detection

Publication Type:
Conference Proceeding
Citation:
Proceedings - 15th International Parallel and Distributed Processing Symposium, IPDPS 2001, 2001, pp. 1359 - 1364
Issue Date:
2001-01-01
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© 2001 IEEE. Image edge detection in computer vision and image processing is a process which detects one kind of significant feature in an image that appears as large delta values in intensities. In this paper, a parallel algorithmic skeleton for edge detection is proposed based on the Spiral Architecture and the Gaussian multi-scale theory. UNIX-based network programming mechanisms in C are used for the implementation on a cluster of Sun-workstations. Our work provides an efficient algorithm for edge detection and is robust to noise.
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