Abstract
Feature detection always is an important problem in image processing. Ridgelet performs very well for objects with linear singularities. Based on the idea of ridgelet, this paper presents an adaptive algorithm for detecting curved feature in anisotropic images. The curve is adaptively partitioned into fragments with different length, and these fragments are nearly straight at fine scales, then it can be detected by using ridgelet transform. Experimental results prove the efficiency of this algorithm.
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© 2004 Springer-Verlag Berlin Heidelberg
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Liu, K., Jiao, L. (2004). Adaptive Curved Feature Detection Based on Ridgelet. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30125-7_61
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DOI: https://doi.org/10.1007/978-3-540-30125-7_61
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23223-0
Online ISBN: 978-3-540-30125-7
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