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https://open.uns.ac.rs/handle/123456789/5224
Nаziv: | Signature of a shape based on its pixel coverage representation | Аutоri: | Ilić, Vladimir Lindblad J. Sladoje N. |
Dаtum izdаvаnjа: | 1-јан-2016 | Čаsоpis: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Sažetak: | © Springer International Publishing Switzerland 2016. Distance from the boundary of a shape to its centroid, a.k.a. signature of a shape, is a frequently used shape descriptor. Commonly, the observed shape results from a crisp (binary) segmentation of an image. The loss of information associated with binarization leads to a significant decrease in accuracy and precision of the signature, as well as its reduced invariance w.r.t. translation and rotation. Coverage information enables better estimation of edge position within a pixel. In this paper, we propose an iterative method for computing the signature of a shape utilizing its pixel coverage representation. The proposed method iteratively improves the accuracy of the computed signature, starting from a good initial estimate. A statistical study indicates considerable improvements in both accuracy and precision, compared to a crisp approach and a previously proposed approach based on averaging signatures over α-cuts of a fuzzy representation. We observe improved performance of the proposed descriptor in the presence of noise and reduced variation under translation and rotation. | URI: | https://open.uns.ac.rs/handle/123456789/5224 | ISBN: | 9783319323596 | ISSN: | 03029743 | DOI: | 10.1007/978-3-319-32360-2_14 |
Nаlаzi sе u kоlеkciјаmа: | FTN Publikacije/Publications |
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