Abstract
Curve matching plays an important role in many applications, such as image registration, 3D reconstruction, object recognition and video understanding. However, compared with other features(such as point, region) matching, it has made little progress in recent years. In this paper, we investigate the problem of automatic curve matching only from their neighborhood appearance. A novel descriptor called HMCD descriptor is proposed for this purpose, which is constructed by the following three steps: (1) Curve neighborhood is divided into a series of overlapped sub-regions with the same size; (2) Curve description matrix (CDM) is formed by characterizing each sub-region into a vector; (3) HMCD descriptor is built by computing the first four order Moments of CDM column vectors. Experimental results show that HMCD descriptor is highly distinctive and very robust for curve matching on real images.
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Wang, Z., Liu, H., Wu, F. (2010). Image Content Based Curve Matching Using HMCD Descriptor. In: Zha, H., Taniguchi, Ri., Maybank, S. (eds) Computer Vision – ACCV 2009. ACCV 2009. Lecture Notes in Computer Science, vol 5996. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12297-2_43
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DOI: https://doi.org/10.1007/978-3-642-12297-2_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12296-5
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