© The Institution of Engineering and Technology
This study proposes a novel shape matching algorithm through exploiting shape contexts. The contributions of the proposed algorithm are twofold: (i) a new framework is presented to deal with the shape matching problem based on shape contexts, but differently from existing methods, the authors exploit a polynomial fitting-based feature point extraction method as a preprocessing step, so as to enhance the performance of the shape contexts-based descriptor; (ii) the authors design a voting classification method based on the chi-square statistical measure to evaluate the matching results. The experimental results show that this method is able to achieve high performance, even if shapes of testing objects suffer from translation, rotation and scaling.
References
-
-
1)
-
11. Petrakis, E.G.M., Diplaros, A., Milios, E.: ‘Matching and retrieval of distorted and occluded shapes using dynamic programming’, IEEE Trans. Pattern Anal. Mach. Intell., 2002, 24, (11), pp. 1501–1516 (doi: 10.1109/TPAMI.2002.1046166).
-
2)
-
2. Blum, H.: ‘A transformation for extracting new descriptors of shape’. Proc. of the Models for the Perception of Speech and Visual Form, Cambridge, MA, 1967, pp. 362–380.
-
3)
-
19. Peng, Q., Zhao, L.: ‘A modified segmentation approach for synthetic aperture radar images on level set’, J. Softw., 2013, 8, (5), pp. 1168–1173 (doi: 10.4304/jsw.8.5.1168-1173).
-
4)
-
14. Belongie, S., Malik, J., Puzicha, J.: ‘Matching shapes’. Proc. of Eighth IEEE Int. Conf. on Computer Vision, Vancouver, British Columbia, Canada, 2001, vol. 1, pp. 454–461.
-
5)
-
7. Sharvit, D., Chan, J., Tek, H., et al: ‘Symmetry-based indexing of image databases’. Proc. of IEEE Workshop on Content-Based Access of Image and Video Libraries, Santa Barbara, CA, 1998, pp. 56–62.
-
6)
-
17. Peng, Q., Zhao, L.: ‘SAR image filtering based on the Cauchy–Rayleigh mixture model’, IEEE Geosc. Remote Sens. Lett., 2014, 11, (5), pp. 960–964 (doi: 10.1109/LGRS.2013.2283258).
-
7)
-
16. Shu, X., Wu, X.J.: ‘A novel contour descriptor for 2D shape matching and its application to image retrieval’, Image Vis. Comput., 2011, 29, (4), pp. 286–294 (doi: 10.1016/j.imavis.2010.11.001).
-
8)
-
12. Bartolini, I., Ciaccia, P., Patella, M.: ‘Warp: Accurate retrieval of shapes using phase of fourier descriptors and time warping distance’, IEEE Trans. Pattern Anal. Mach. Intell., 2005, 27, (1), pp. 142–147 (doi: 10.1109/TPAMI.2005.21).
-
9)
-
8. Sebastian, T.B., Klein, P.N., Kimia, B.B.: ‘Recognition of shapes by editing their shock graphs’, IEEE Trans. Pattern Anal. Mach. Intell., 2004, 26, (5), pp. 550–571 (doi: 10.1109/TPAMI.2004.1273924).
-
10)
-
5. Zhang, H., Liu, Y., Ma, Z.: ‘Fusing inherent and external knowledge with nonlinear learning for cross-media retrieval’, Neurocomputing, 2013, 119, pp. 10–16 (doi: 10.1016/j.neucom.2012.03.033).
-
11)
-
15. Xu, C., Liu, J., Tang, X.: ‘2D shape matching by contour flexibility’, IEEE Trans. Pattern Anal. Mach. Intell., 2009, 31, (1), pp. 180–186 (doi: 10.1109/TPAMI.2008.199).
-
12)
-
4. Sebastian, T.B., Klein, P.N., Kimia, B.B.: ‘On aligning curves’, IEEE Trans. Pattern Anal. Mach. Intell., 2003, 25, (1), pp. 116–125 (doi: 10.1109/TPAMI.2003.1159951).
-
13)
-
16. Belongie, S., Malik, J., Puzicha, J.: ‘Shape matching and object recognition using shape contexts’, IEEE Trans. Pattern Anal. Mach. Intell., 2002, 24, (4), pp. 509–522 (doi: 10.1109/34.993558).
-
14)
-
9. Siddiqi, K., Shokoufandeh, A., Dickinson, S.J., et al: ‘Shock graphs and shape matching’, Int. J. Comput. Vis., 1999, 35, (1), pp. 13–32 (doi: 10.1023/A:1008102926703).
-
15)
-
1. Kim, W., Kim, Y.: ‘A region-based shape descriptor using zernike moments’, Signal Process. Image Commun., 2000, 16, (1–2), pp. 95–102 (doi: 10.1016/S0923-5965(00)00019-9).
-
16)
-
10. Gdalyahu, Y., Weinshall, D.: ‘Flexible syntactic matching of curves and its application to automatic hierarchical classification of silhouettes’, IEEE Trans. Pattern Anal. Mach. Intell., 1999, 21, (12), pp. 1312–1328 (doi: 10.1109/34.817410).
-
17)
-
3. Sebastian, T.B., Kimia, B.B.: ‘Curves vs. skeletons in object recognition’, Signal Process., 2005, 85, (2), pp. 247–263 (doi: 10.1016/j.sigpro.2004.10.016).
-
18)
-
18. Peng, Q., Zhao, L.: ‘Novel mixture model for synthetic aperture radar imagery’, J. Appl. Remote Sens., 2012, 6, (1), pp. 1–16 (doi: 10.1117/1.JRS.6.063616).
-
19)
-
6. Liu, T.L., Geiger, D.: ‘Approximate tree matching and shape similarity’. Proc. of the Seventh IEEE Int. Conf. on Computer Vision, Kerkyra, Greece, 1999, pp. 456–462.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cvi.2014.0159
Related content
content/journals/10.1049/iet-cvi.2014.0159
pub_keyword,iet_inspecKeyword,pub_concept
6
6