A SIFT-Color moments descriptor for object recognition
- Authors
- Bo, L.; Whangbo, T.
- Issue Date
- 2014
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- Color Moment; feature descriptor; invariant feature; Object Recognition; SIFT
- Citation
- 2014 International Conference on IT Convergence and Security, ICITCS 2014
- Journal Title
- 2014 International Conference on IT Convergence and Security, ICITCS 2014
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/13122
- DOI
- 10.1109/ICITCS.2014.7021716
- ISSN
- 0000-0000
- Abstract
- Feature extraction technique has been widely studied and used in many fields, such as Augmented Reality, 3D Reconstruction and object recognition. In recent years, intensity-based descriptor have been widely used for feature extraction, and the SIFT descriptor is the most robust of them. However the color information is not included in SIFT, and the color provides important information in object description and matching tasks. SIFT can't differentiate the objects with similar shape but with different colors commendably. Many objects can be misclassified in object recognition without color information. Therefore, this paper proposes a novel descriptor combine SIFT with Color Moments to improve the performance of object recognition, and so called SIFT-Color Moments Descriptor. Experimental results show that the SIFT-Color Moments Descriptor is more robust than the traditional SIFT with color image. © 2014 IEEE.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - IT융합대학 > 컴퓨터공학과 > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/13122)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.