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| Longin Jan Latecki, Rolf Lakämper, "Shape Similarity Measure Based on Correspondence of Visual Parts," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 10, pp. 1185-1190, October, 2000. | |||
| BibTex | x | ||
| @article{ 10.1109/34.879802, author = {Longin Jan Latecki and Rolf Lakämper}, title = {Shape Similarity Measure Based on Correspondence of Visual Parts}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {22}, number = {10}, issn = {0162-8828}, year = {2000}, pages = {1185-1190}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.879802}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - JOUR JO - IEEE Transactions on Pattern Analysis and Machine Intelligence TI - Shape Similarity Measure Based on Correspondence of Visual Parts IS - 10 SN - 0162-8828 SP1185 EP1190 EPD - 1185-1190 A1 - Longin Jan Latecki, A1 - Rolf Lakämper, PY - 2000 KW - Shape representation KW - shape similarity measure KW - visual parts KW - discrete curve evolution. VL - 22 JA - IEEE Transactions on Pattern Analysis and Machine Intelligence ER - | |||
Abstract—A cognitively motivated similarity measure is presented and its properties are analyzed with respect to retrieval of similar objects in image databases of silhouettes of 2D objects. To reduce influence of digitization noise, as well as segmentation errors, the shapes are simplified by a novel process of digital curve evolution. To compute our similarity measure, we first establish the best possible correspondence of visual parts (without explicitly computing the visual parts). Then, the similarity between corresponding parts is computed and aggregated. We applied our similarity measure to shape matching of object contours in various image databases and compared it to well-known approaches in the literature. The experimental results justify that our shape matching procedure gives an
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