| A novel description based on skeleton and contour for shape matching | |
| Hu, Jinlong1,2; Peng, Xianrong1; Fu, Chengyu1 | |
| Volume | 9255 |
| Pages | 925541 |
| 2015 | |
| Language | 英语 |
| ISSN | 0277-786X |
| DOI | 10.1117/12.2065209 |
| Indexed By | SCI ; Ei |
| Subtype | 会议论文 |
| 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. © 2015 SPIE.; 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. © 2015 SPIE. |
| Conference Name | Proceedings of SPIE: 20th International Symposium on High Power Systems and Applications 2014, HPLS and A 2014 |
| Conference Date | 2015 |
| Citation statistics | |
| Document Type | 会议论文 |
| Identifier | http://ir.ioe.ac.cn/handle/181551/7440 |
| Collection | 光电工程总体研究室（一室） |
| Corresponding Author | Hu, Jinlong |
| Affiliation | 1. Institute of Optics and Electronics, Key Laboratory of Beam Control, Chinese Academy of Sciences, Chengdu, Sichuan, China 2. University of Chinese Academy of Sciences, Beijing, China |
| Recommended Citation GB/T 7714 | Hu, Jinlong,Peng, Xianrong,Fu, Chengyu. A novel description based on skeleton and contour for shape matching[C],2015:925541. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| 2015-2053.pdf（270KB） | 会议论文 | 开放获取 | CC BY-NC-SA | Application Full Text | ||
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