CAIP 2013: Computer Analysis of Images and Patterns pp 1-8 | Cite as
Classified-Distance Based Shape Descriptor for Application to Image Retrieval
Conference paper
Abstract
We propose a method to improve the quality and the query time of shape-based image retrieval. We define a novel and an accurate shape descriptor named Distance Interior Ratio (DIR) that is invariant to rigid motion and scaling. The DIR of shapes can also be stored in an efficient search structure. Our experimental result shows a higher retrieval rate and efficient query time.
Keywords
2D Shape Description Image Retrieval Shape RecognitionPreview
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References
- 1.Belongie, S., Malik, J., Puzicha, J.: Shape Matching and Object Recognition Using Shape Contexts. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(24), 509–522 (2002)CrossRefGoogle Scholar
- 2.Gionis, A., Indyk, P., Motwani, R.: Similarity Search in High Dimensions via Hashing. In: Proceedings of the 25th International Conference on Very Large Data Basess, pp. 518–529 (1999)Google Scholar
- 3.Bresenham, J.E.: Algorithm for computer control of a digital plotter. IBM Systems Journal 4(1), 25–30 (1965)CrossRefGoogle Scholar
- 4.Ling, H., Jacobs, D.W.: Shape Classification Using Inner-Distance. IEEE Trans. Pattern Analysis and Machine Intelligence 29(2), 286–299 (2007)CrossRefGoogle Scholar
- 5.LSH package, http://ttic.uchicago.edu/gregory/download.html
- 6.Ip, C.Y., Lapadat, D., Sieger, L., Regil, W.C.: Using Shape Distributions to Compare Solid Models. In: Symposium on Solid Modeling and Applications, pp. 273–280 (2002)Google Scholar
- 7.Latecki, L.J., Lakamper, R., Eckhardt, U.: Shape Descriptors for Non-rigid Shapes with a Single Closed Controur. In: IEE Conf. on Computer Vision and Pattern Recognition, pp. 424–429 (2000)Google Scholar
- 8.Osada, R., Funkhouser, T., Chazelle, B., Dobkin, D.: Shape Distributions. ACM Transctions on Graphics 21, 807–832 (2002)CrossRefGoogle Scholar
- 9.Rosin, P.L., Mumford, C.L.: A Symmetric Convexity Measure. Computer Vision and Image Understanding 103, 101–111 (2006)CrossRefGoogle Scholar
- 10.Sebastian, T.B., Klein, P.N., Kimia, B.B.: Recognition of Shapes by Editing Their Shock Graphs. IEEE Trans. Pattern anal. Mach. Intell. 26(5), 550–571 (2004)CrossRefGoogle Scholar
- 11.Shakhnarovich, G., Darrel, T., Indyk, P.: Nearest-Neighbor Methods in Learning and Vision Theory and Practise. MIT Press (March 2006)Google Scholar
- 12.Skiena, S.S., Smith, W.D., Lemke, P.: Reconstructing Sets From Interpoint Distances (extended abstract). In: The 6th Annual Symposium on Computational Geometry, pp. 332–339 (1990)Google Scholar
- 13.Mingqiang, Y., Idiyo, K.K., Joseph, R.: A Survey of Shape Feature Extraction Techniques. Pattern Recognition Techniques 24(2), 626–664 (2008)Google Scholar
- 14.Zhang, D., Lu, G.: Review of Shape Representation and Description Techniques. Pattern Recognition, 1–19 (2003)Google Scholar
- 15.Shu, X., Wu, X.J.: A Novel Contour Descriptor for 2D Shape Matching and Its Application to Image Retrieval. Image and Vision Computing 29, 286–294 (2011)CrossRefGoogle Scholar
- 16.Zhang, D., Lu, G.: A Comparative Study of Fourier Descriptors for Shape Representation and Retrieval. In: The 5th Asian Conference on Computer Vision, pp. 646–651 (2002)Google Scholar
- 17.Zhang, J., Wenyin, L.: A Pixel-level Statistical Structural Descriptor for Shape Measure and Recognition. In: The 10th International Conference on Document Analysis and Recognition, pp. 386–390 (2009)Google Scholar
- 18.Zunic, J., Rosin, P.L.: A Convexity Measurement for Polygons. IEEE Trans. Pattern Anal. Mach. Intell. 26, 173–182 (2002)Google Scholar
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