標題: A Zernike Moment Phase-Based Descriptor for Local Image Representation and Matching
作者: Chen, Zen
Sun, Shu-Kuo
資訊工程學系
Department of Computer Science
關鍵字: Geometric and photometric transformations;image representation and matching;performance evaluation;phase and magnitude components;precision and recall;region descriptors;Zernike moments (ZM)
公開日期: 1-一月-2010
摘要: A local image descriptor robust to the common photometric transformations (blur, illumination, noise, and JPEG compression) and geometric transformations ( rotation, scaling, translation, and viewpoint) is crucial to many image understanding and computer vision applications. In this paper, the representation and matching power of region descriptors are to be evaluated. A common set of elliptical interest regions is used to evaluate the performance. The elliptical regions are further normalized to be circular with a fixed size. The normalized circular regions will become affine invariant up to a rotational ambiguity. Here, a new distinctive image descriptor to represent the normalized region is proposed, which primarily comprises the Zernike moment (ZM) phase information. An accurate and robust estimation of the rotation angle between a pair of normalized regions is then described and used to measure the similarity between two matching regions. The discriminative power of the new ZM phase descriptor is compared with five major existing region descriptors ( SIFT, GLOH, PCA-SIFT, complex moments, and steerable filters) based on the precision-recall criterion. The experimental results, involving more than 15 million region pairs, indicate the proposed ZM phase descriptor has, generally speaking, the best performance under the common photometric and geometric transformations. Both quantitative and qualitative analyses on the descriptor performances are given to account for the performance discrepancy. First, the key factor for its striking performance is due to the fact that the ZM phase has accurate estimation accuracy of the rotation angle between two matching regions. Second, the feature dimensionality and feature orthogonality also affect the descriptor performance. Third, the ZM phase is more robust under the nonuniform image intensity fluctuation. Finally, a time complexity analysis is provided.
URI: http://dx.doi.org/10.1109/TIP.2009.2032890
http://hdl.handle.net/11536/6156
ISSN: 1057-7149
DOI: 10.1109/TIP.2009.2032890
期刊: IEEE TRANSACTIONS ON IMAGE PROCESSING
Volume: 19
Issue: 1
起始頁: 205
結束頁: 219
顯示於類別:期刊論文


文件中的檔案:

  1. 000272844000019.pdf