An Improved SURF Algorithm based Local Image Symmetry Scoring Scheme
文献类型：会议论文
| 作者 | Ma, Linwei; Song, Zhan; Zhu, Guohun |
| 出版日期 | 2014 |
| 会议名称 | Image and Signal Processing (CISP), 2014 7th International Congress on |
| 会议地点 | 中国 |
| 英文摘要 | This paper presents an efficient feature detection algorithm based on the classical SURF (Speeded Up Robust Feature) detector. The image features are represented and scored with respect to its local symmetry property. The local symmetry has natural properties of scale and transformation invariants, and also insensitive to illumination change and local noise. By the proposed feature descriptor, the calculation of 64-dimensional vectors in SURF algorithm can be reduced to 16-dimensional vector respectively. The local symmetry score is defined as the sum of minimum distance between each feature point and its neighboring points in an image based on the image intensities. The algorithm is experimented with some real images and the results are compared with the original SURF algorithm to show its improvement. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/5620]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | 2014 |
| 推荐引用方式 GB/T 7714 | Ma, Linwei,Song, Zhan,Zhu, Guohun. An Improved SURF Algorithm based Local Image Symmetry Scoring Scheme[C]. 见:Image and Signal Processing (CISP), 2014 7th International Congress on. 中国. |
入库方式： OAI收割
来源：深圳先进技术研究院
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