Abstract
Applying an edge detector to an image, in the ideal case, may obtain a set of connected curves which indicate the boundaries of objects. Actually edges in an image are a collection of pixels which are recognized as an edge in surface orientation. This paper proposes a new edge detect algorithm which uses PSO (Particle Swarm Optimization) for detection of best fitness curves in an image that represent boundaries of objects. To improve the speed of edge use the PSO on the pixels whose gradient grate than the threshold. Use image with simple geometric objects, with impulse noise levels and the image have complex texture to assess the system. Use this algorithm on the images with high noise levels to detect edge is more accurately than existing edge detector.
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Chen, D., Zhou, T., Yu, X. (2012). A New Method of Edge Detection Based on PSO. In: Wang, J., Yen, G.G., Polycarpou, M.M. (eds) Advances in Neural Networks – ISNN 2012. ISNN 2012. Lecture Notes in Computer Science, vol 7368. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31362-2_27
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DOI: https://doi.org/10.1007/978-3-642-31362-2_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31361-5
Online ISBN: 978-3-642-31362-2
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