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논문검색

Comparative Analysis of Wavelet-Based Scale-Invariant Feature Extraction Using Different Wavelet Bases

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

저자정보

  • Joohyun Lim Image Processing and Intelligent Systems Laboratory, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University
  • Youngouk Kim Image Processing and Intelligent Systems Laboratory, Graduate School of Advanced Intelligent Robotics Research Laboratory, Korea Electronics Technology Institute
  • Joonki Paik Image Processing and Intelligent Systems Laboratory, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University

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