Graph Structuring of Skeleton Object for Its High-Level Exploitation

Skeletonization is a morphological operation that summarizes an object by its median lines while preserving the initial image topology. It provides features used in biometric for the matching process, as well as medical imaging for quantification of the bone microarchitecture. We develop a solution for the extraction of structural and morphometric features useful in biometric, character recognition and medical imaging. It aims at storing object descriptors in a re-usable and hierarchical format. We propose graph data structures to identify skeleton nodes and branches, link them and store their corresponding features. This graph structure allows us to generate CSV files for high level analysis and to propose a pruning method that removes spurious branches regarding their length and mean gray level. We illustrate manipulations of the skeleton graph structure on medical image dedicated to bone microarchitecture characterization.

[1]  Xiaoou Tang,et al.  Preprocessing and postprocessing for skeleton-based fingerprint minutiae extraction , 2007, Pattern Recognit..

[2]  F Peyrin,et al.  Subchondral bone micro-architectural alterations in osteoarthritis: a synchrotron micro-computed tomography study. , 2006, Osteoarthritis and cartilage.

[3]  Jonathan L. Gross,et al.  Graph Theory and Its Applications, Second Edition (Discrete Mathematics and Its Applications) , 2005 .

[4]  Ali Shokoufandeh,et al.  Shock Graphs and Shape Matching , 1998, International Journal of Computer Vision.

[5]  Amel Benazza-Benyahia,et al.  Texture Image Analysis for Osteoporosis Detection with Morphological Tools , 2004, MICCAI.

[6]  Cecilia Di Ruberto,et al.  Recognition of shapes by attributed skeletal graphs , 2004, Pattern Recognit..

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

[8]  Sylvie Sevestre,et al.  Statitical control of thinning algorithm with implementation based on hierarchical queues , 2014, 2014 6th International Conference of Soft Computing and Pattern Recognition (SoCPaR).

[9]  Gilles Bertrand,et al.  Gray-scale image processing using topological operators , 1999, Optics & Photonics.

[10]  Milan Sonka,et al.  Segmentation, Skeletonization, and Branchpoint Matching - A Fully Automated Quantitative Evaluation of Human Intrathoracic Airway Trees , 2002, MICCAI.

[11]  Venu Govindaraju,et al.  Segmentation of Arabic Handwriting Based on both Contour and Skeleton Segmentation , 2009, 2009 10th International Conference on Document Analysis and Recognition.

[12]  Di Huang,et al.  Hand Dorsal Vein Recognition Based on Hierarchically Structured Texture and Geometry Features , 2012, CCBR.