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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yi Song Yiping Shen Shuxiao Li Chengfei Zhu Jinglan Zhang Hongxing Chang |
| Copyright Year | 2014 |
| Description | Author affiliation: Integrated Inf. Syst. Res. Center, Inst. of Autom., Beijing, China (Yi Song; Yiping Shen; Shuxiao Li; Chengfei Zhu; Hongxing Chang) || Queensland Univ. of Technol., Brisbane, QLD, Australia (Jinglan Zhang) |
| Abstract | Corner detection has shown its great importance in many computer vision tasks. However, in real-world applications, noise in the image strongly affects the performance of corner detectors. Few corner detectors have been designed to be robust to heavy noise by now, partly because the noise could be reduced by a denoising procedure. In this paper, we present a corner detector that could find discriminative corners in images contaminated by noise of different levels, without any denoising procedure. Candidate corners (i.e., features) are firstly detected by a modified SUSAN approach, and then false corners in noise are rejected based on their local characteristics. Features in flat regions are removed based on their intensity centroid, and features on edge structures are removed using the Harris response. The detector is self-adaptive to noise since the image signal-to-noise ratio (SNR) is automatically estimated to choose an appropriate threshold for refining features. Experimental results show that our detector has better performance at locating discriminative corners in images with strong noise than other widely used corner or key point detectors. |
| Starting Page | 906 |
| Ending Page | 911 |
| File Size | 1050058 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479952090 |
| ISSN | 10514651 |
| DOI | 10.1109/ICPR.2014.166 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-08-24 |
| Publisher Place | Sweden |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Detectors Signal to noise ratio Noise measurement Feature extraction Noise level Estimation feature detection corner detector noisy image signal-to-noise ratio |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition |
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