Share Email Print

Proceedings Paper

A novel description based on skeleton and contour for shape matching
Author(s): Jinlong Hu; Xianrong Peng; Chengyu Fu
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

In computer vision field, feature extraction plays a critical role in shape matching, image alignment, object recognition and tracking etc. Generally speaking, feature extraction consists of three steps: feature detection, feature description and feature matching. In the second step, the detected features (e.g. gray value, SIFT, Harris corners) are converted to vectors or the form that can be described mathematically such that feature can be matched correctly. How to construct an efficient descriptor to realize accurate shape matching under a variety of transformations is still a challenge. To this end, a novel shape descriptor based on skeleton for shape matching is proposed in this paper. Firstly, the image is smoothed with Gaussian filter to remove the influence of the noise. Secondly, the smoothed image is segmented with Fuzzy C-means Cluster (FCM) to obtain a binary image. Thirdly, the binary image’s skeleton is extracted with Medial Axis Transform (MAT), thus the skeleton’s endpoints and joint-points locations are acquired. Furthermore, the object’s contour is extracted with contour coding. In the construction of skeletal descriptor, the relative location vectors of the skeletal endpoints to each contour point are computed. Being similar to shape context, statistical histogram is constructed in log-polar coordinate. Consequently, shape matching is performed via two histograms’ similarity measurement. Experiments on standard MPEG7 dataset show that the proposed shape description method allows translation, scale and rotation invariance.

Paper Details

Date Published: 3 February 2015
PDF: 9 pages
Proc. SPIE 9255, XX International Symposium on High-Power Laser Systems and Applications 2014, 925541 (3 February 2015); doi: 10.1117/12.2065209
Show Author Affiliations
Jinlong Hu, Institute of Optics and Electronics (China)
Univ of Chinese Academy of Sciences (China)
Xianrong Peng, Institute of Optics and Electronics (China)
Chengyu Fu, Institute of Optics and Electronics (China)

Published in SPIE Proceedings Vol. 9255:
XX International Symposium on High-Power Laser Systems and Applications 2014
Chun Tang; Shu Chen; Xiaolin Tang, Editor(s)

© SPIE. Terms of Use
Back to Top