On Image Analysis by the Methods of Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Invariant Image Recognition by Zernike Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computation of component image velocity from local phase information
International Journal of Computer Vision
The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Representation Using 2D Gabor Wavelets
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Rotation Angle Estimator
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stability of Phase Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Affine/ Photometric Invariants for Planar Intensity Patterns
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Multi-view Matching for Unordered Image Sets, or "How Do I Organize My Holiday Snaps?"
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Plane-based Calibration Algorithm for Multi-camera Systems via Factorization of Homography Matrices
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Matching Widely Separated Views Based on Affine Invariant Regions
International Journal of Computer Vision
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Sparse Texture Representation Using Local Affine Regions
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Comparison of Affine Region Detectors
International Journal of Computer Vision
A novel approach to the fast computation of Zernike moments
Pattern Recognition
Local Descriptor by Zernike Moments for Real-Time Keypoint Matching
CISP '08 Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 2 - Volume 02
PCA-SIFT: a more distinctive representation for local image descriptors
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Multi-scale phase-based local features
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Accurate and efficient computation of high order zernike moments
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
Accurate Computation of Zernike Moments in Polar Coordinates
IEEE Transactions on Image Processing
Orthogonal Rotation-Invariant Moments for Digital Image Processing
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
Real-time computation of Zernike moments
IEEE Transactions on Circuits and Systems for Video Technology
Classification of benign and malignant masses based on Zernike moments
Computers in Biology and Medicine
Image recognition by affine Tchebichef moment invariants
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part III
Accurate calculation of Zernike moments
Information Sciences: an International Journal
An improvement to the SIFT descriptor for image representation and matching
Pattern Recognition Letters
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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.