원문정보
보안공학연구지원센터(IJSIP)
International Journal of Signal Processing, Image Processing and Pattern Recognition
vol.2 no.4
2009.12
pp.29-38
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
In this paper, we present comparative analysis of scale-invariant feature extraction using different wavelet bases. The main advantage of the wavelet transform is the multi-resolution analysis. Furthermore, wavelets enable localization in both space and frequency domains and high-frequency salient feature detection. Wavelet transforms can use various basis functions. This research aims at comparative analysis of Haar, Daubechies and Gabor wavelets for scale-invariant feature extraction. Experimental results show that Gabor wavelets outperform better than Haar, Daubechies wavelets in the sense of both objective and subjective measures.
목차
Abstract
1. Introduction
2. Comparison of Feature Extraction Performance Using DifferentWavelet Bases
2.1. Feature extraction using the Haar and Daubechies wavelet
2.2. Feature extraction using Gabor wavelet
3. Experiment Results
5. Conclusion
References
1. Introduction
2. Comparison of Feature Extraction Performance Using DifferentWavelet Bases
2.1. Feature extraction using the Haar and Daubechies wavelet
2.2. Feature extraction using Gabor wavelet
3. Experiment Results
5. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보
