On Image Analysis by the Methods of Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
3-D Moment Forms: Their Construction and Application to Object Identification and Positioning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Moment-based texture segmentation
Pattern Recognition Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image analysis by Tchebichef moments
IEEE Transactions on Image Processing
Image analysis by Krawtchouk moments
IEEE Transactions on Image Processing
Image Analysis Using Hahn Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature-based watermarking using discrete orthogonal Hahn moment invariants
Proceedings of the 7th International Conference on Frontiers of Information Technology
CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
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Orthogonal moments are recognized as useful tools for object representation and image analysis. It has been shown that the recently developed discrete orthogonal moments have better performance than the conventional continuous orthogonal moments. In this paper, a new set of discrete orthogonal polynomials, namely Hahn polynomials, are introduced. The related Hahn moment functions defined on this orthogonal basis set are investigated and applied to image reconstruction. In experiments, the Hahn moments are compared with the other two discrete orthogonal moments: Chebyshev and Krawtchouk moments. The simulation results show that the Hahn moment-based reconstruction method is superior to the other two discrete orthogonal moment-based methods.