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Conference Paper
Fast Image Retrieval with Grid-based Keypoint Detector and Binary Descriptor
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- Authors
- SuGil Choi, SeungWan Han
- Issue Date
- 2014-10
- Citation
- International Conference on Information and Communication Technology Convergence (ICTC) 2014, pp.679-680
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- As an alternative to vector-based descriptors, such as SIFT and SURF, more computationally efficient binary descriptors, such as BRISK and ORB, have recently been proposed. These binary descriptors are usually used in combination with a novel scale-space FAST-based detector to be suitable for real-time applications, but it consumes more time than creating binary descriptors. Therefore, if accuracy can be kept similar, keypoint sampling by a grid is better than FAST-based detector because it consumes almost no time. In this paper, grid-based sampling and BRISK keypoint detector are tested for image retrieval. Experimental results demonstrate that grid-based sampling out performs keypoint detector in terms of accuracy and processing speed.
- KSP Keywords
- Computationally Efficient, Fast image retrieval, Keypoint detector, Processing speed, Real-Time applications, SIFT and SURF, Scale space, binary descriptors, grid-based sampling