- Title
- Improving SIFT's performance by incorporating appropriate gradient information
- Creator
- Lv, Guohua; Hossain, Md. Tanvir; Teng, Shyh; Lu, Guojun; Lackmann, Martin
- Date
- 2011
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/161011
- Identifier
- vital:12357
- Abstract
- Scale Invariant Feature Transform (SIFT) has been applied in numerous applications especially in the domain of computer vision. In these applications, image information used for building the SIFT descriptor can have a significant impact on its performance. When building orientation histograms for descriptors, a critical step is how to increment the values in the orientation bins. The original scheme for this step in SIFT was improved in [6]. Two different types of gradient information are used for building orientation histograms. The limitations of the two schemes are identified in this paper and we then propose three new schemes which use both types of gradient information in the feature description and matching stages. Our experimental results show that the proposed schemes can achieve better registration performances than the schemes proposed in SIFT and [6].
- Publisher
- Image and Vision Computing New Zealand
- Relation
- 26th Image and Vision Computing New Zealand Conference (IVCNZ 2011) p. 381 - 386
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0801 Artificial Intelligence and Image Processing; SIFT; Image registration; Keypoint description and matching
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