Abstract
This paper introduces a novel shape descriptor invariant to rotation and scale, namely centroid-based tree-structured (CbTs), for measuring shape similarity. For obtaining CbTs descriptor, first, the central of mass of a binary shape is computed. It will be regarded as the root node of tree. The shape is divided into b sub-shapes by voting each foreground pixel point based on angle between point and major principal axis. In the same way, the central of masses of the sub-shapes are calculated and these locations are considered as level-1 nodes. These processes are repeated for a predetermined number of levels. For each node corresponding to sub-shapes, five parameters invariant to translation, rotation and scale are extracted. Thus, a vector of all parameters is carried out as descriptor. To measure dissimilarity between shapes, we employ vector-based template matching with X 2 distance measurement. Results are presented for MPEG-7 dataset.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Veltkamp, R.C.: Shape matching: similarity measures and algorithms. In: Proceeding of International Conference on Shape Modeling and Applications, pp. 188–197 (May 2001)
Jeannin, S., Bober, M.: Description of core experiments for MPEG-7 motions/shape. Technical report ISO/IEC JTC 1/SC/29/WG 11 MPEG99/N2690, MPEG-7, Seoul (March 1999)
Sharvit, D., Chan, J., Tek, H., Kimia, B.: Symmetry-based indexing of image databases. J. Visual Communication and Image Representation (1998)
Hu, M.K.: Visual Pattern Recognition by Moment Invariants. IRE Trans. Information Theory 8, 179–197 (1962)
Kim, Y.S., Kim, W.Y.: Content-Based Trademark Retrieval System Using a Visually Salient Feature. Image and Vision Computing 16(12-13), 931–939 (1998)
Jain, A.K., Vailaya, A.: Shape-Based Retrieval: A Case Study with Trademark Image Databases. Pattern Recognition 31(9), 1369–1390 (1998)
Alajlan, N., Kamel, M., Freeman, G.: Geometry-based image retrieval in binary image databases. IEEE Trans. on PAMI 30(6), 1003–1013 (2008)
Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape context. IEEE Transaction on Pattern Analysis and Machine Intelligence 24(24), 509–522 (2002)
Ling, H., Jacobs, D.: Shape classification using the inner-distance. IEEE Transaction on Pattern Analysis and Machine Intelligence 29(2), 286–299 (2007)
Thakoor, N., Gao, J., Jung, S.: Hidden Markov Model-Based Weighted Likelihood Discriminant for 2-D Shape Classification. IEEE Transactions on Image Processing 16(11), 2707–2719 (2007)
Kim, H.-K., Kim, J.-D.: Region-based shape descriptor invariant to rotation, scale and translation. Signal Processing: Image Communication 16, 87–93 (2000)
Bicego, M., Murino, V.: Investigating hidden Markov models’ capabilities in 2-D shape classification. IEEE Transaction on Pattern Analysis and Machine Intelligence 26(2), 281–286 (2004)
Bai, X., Yang, X., Latecki, L.J., Liu, W., Tu, Z.: Learning Context Sensitive Shape Similarity by Graph Transduction. IEEE Trans. Pattern Analysis and Machine Intelligence, PAMI (2009)
Xie, J., Heng, P., Shah, M.: Shape matching and modeling using skeletal context. Pattern Recognition 41(5), 1756–1767 (2008)
Grigorescu, C., Petkov, N.: Distance sets for shape filters and shape recognition. IEEE Trans. on Image Processing 12(7), 729–739 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Wahyono, Kurnianggoro, L., Hariyono, J., Jo, KH. (2014). Similarity-Based Classification of 2-D Shape Using Centroid-Based Tree-Structured Descriptor. In: Ali, M., Pan, JS., Chen, SM., Horng, MF. (eds) Modern Advances in Applied Intelligence. IEA/AIE 2014. Lecture Notes in Computer Science(), vol 8482. Springer, Cham. https://doi.org/10.1007/978-3-319-07467-2_30
Download citation
DOI: https://doi.org/10.1007/978-3-319-07467-2_30
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07466-5
Online ISBN: 978-3-319-07467-2
eBook Packages: Computer ScienceComputer Science (R0)