A Graph-Based Approach for Shape Skeleton Analysis

This paper presents a novel methodology to shape characterization, where a shape skeleton is modeled as a dynamic graph, and degree measurements are computed to compose a set of shape descriptors. The proposed approach is evaluated in a classification experiment which considers a generic set of shapes. A comparison with traditional shape analysis methods, such as Fourier descriptors, Curvature, Zernike moments and Multi-scale Fractal Dimension, is also performed. Results show that the method is efficient for shape characterization tasks, in spite of the reduced amount of information present in the shape skeleton.

[1]  Keinosuke Fukunaga,et al.  Introduction to Statistical Pattern Recognition , 1972 .

[2]  HARRY BLUM,et al.  Shape description using weighted symmetric axis features , 1978, Pattern Recognit..

[3]  Wen-Yen Wu,et al.  Detecting the Dominant Points by the Curvature-Based Polygonal Approximation , 1993, CVGIP Graph. Model. Image Process..

[4]  Wenyu Liu,et al.  Skeleton Pruning by Contour Partitioning with Discrete Curve Evolution , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  B. Everitt,et al.  Applied Multivariate Data Analysis: Everitt/Applied Multivariate Data Analysis , 2001 .

[6]  Keinosuke Fukunaga,et al.  Introduction to statistical pattern recognition (2nd ed.) , 1990 .

[7]  V. Latora,et al.  Complex networks: Structure and dynamics , 2006 .

[8]  Xiangbin Zhu,et al.  Shape Recognition Based on Skeleton and Support Vector Machines , 2007, ICIC.

[9]  Kin-Man Lam,et al.  Extraction of the Euclidean skeleton based on a connectivity criterion , 2003, Pattern Recognit..

[10]  O. Bruno,et al.  Leaf shape analysis using the multiscale Minkowski fractal dimension, a new morphometric method: a study with Passiflora (Passifloraceae) , 2005 .

[11]  M. Zhenjiang.  Zernike moment-based image shape analysis and its application , 2000 .

[12]  Benjamin B. Kimia,et al.  Symmetry-Based Indexing of Image Databases , 1998, J. Vis. Commun. Image Represent..

[13]  Soundar R. T. Kumara,et al.  A skeleton and neural network-based approach for identifying cosmetic surface flaws , 1995, IEEE Trans. Neural Networks.

[14]  Stanislaw Osowski,et al.  Fourier and wavelet descriptors for shape recognition using neural networks - a comparative study , 2002, Pattern Recognit..

[15]  L. da F. Costa,et al.  Characterization of complex networks: A survey of measurements , 2005, cond-mat/0505185.

[16]  Longin Jan Latecki,et al.  Path Similarity Skeleton Graph Matching , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  R. Brubaker.  Models for the perception of speech and visual form: Weiant Wathen-Dunn, ed.: Cambridge, Mass., The M.I.T. Press, I–X, 470 pages , 1968 .

[18]  P. Stadler,et al.  Centers of complex networks. , 2003, Journal of theoretical biology.

[19]  Philip N. Klein,et al.  Recognition of shapes by editing their shock graphs , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[20]  André Ricardo Backes,et al.  A complex network-based approach for boundary shape analysis , 2009, Pattern Recognit..

[21]  Luciano da Fontoura Costa,et al.  A graph-based approach for multiscale shape analysis , 2004, Pattern Recognit..

[22]  Benjamin B. Kimia,et al.  Curves vs. skeletons in object recognition , 2005, Signal Process..