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Detail
Journal Article
blur invariant feature descriptor using multidirectional integral projection
- Authors
- Man Hee Lee, In Kyu Park
- Issue Date
- 2016-06
- Citation
- ETRI Journal, v.38, no.3, pp.502-509
- ISSN
- 1225-6463
- Publisher
- 한국전자통신연구원 (ETRI)
- Language
- English
- Type
- Journal Article
- Abstract
- Feature detection and description are key ingredients of common image processing and computer vision applications. Most existing algorithms focus on robust feature matching under challenging conditions, such as inplane rotations and scale changes. Consequently, they usually fail when the scene is blurred by camera shake or an object's motion. To solve this problem, we propose a new feature description algorithm that is robust to image blur and significantly improves the feature matching performance. The proposed algorithm builds a feature descriptor by considering the integral projection along four angular directions (0째 , 45째 , 90째 , and 135째 ) and by combining four projection vectors into a single highdimensional vector. Intensive experiment shows that the proposed descriptor outperforms existing descriptors for different types of blur caused by linear motion, nonlinear motion, and defocus. Furthermore, the proposed descriptor is robust to intensity changes and image rotation .
- KSP Keywords
- Camera shake, Computer Vision(CV), Feature Description, Feature descriptor, Image blur, Image processing(IP), Image rotation, Integral projection, Invariant feature, Matching performance, Nonlinear motion