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Adaptive Curved Feature Detection Based on Ridgelet

  • Conference paper
Image Analysis and Recognition (ICIAR 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3211))

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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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References

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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

  • eBook Packages: Springer Book Archive

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