Towards absolute invariants of images under translation, rotation, and dilation
Pattern Recognition Letters
A complete invariant description for gray-level images by the harmonic analysis approach
Pattern Recognition Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Representations that uniquely characterize images modulo translation, rotation, and scaling
Pattern Recognition Letters
Generalized Affine Invariant Image Normalization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Probabilistic Visual Learning for Object Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Example-Based Learning for View-Based Human Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Discrete-time signal processing (2nd ed.)
Discrete-time signal processing (2nd ed.)
Computer Vision and Image Understanding
Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Cognitive Neuroscience
RST-invariant digital image watermarking based on log-polar mapping and phase correlation
IEEE Transactions on Circuits and Systems for Video Technology
Expert Systems with Applications: An International Journal
Invariant 2D object recognition using KRA and GRA
Expert Systems with Applications: An International Journal
Identifying objects in range data based on similarity transformation invariant shape signatures
PerMIS '08 Proceedings of the 8th Workshop on Performance Metrics for Intelligent Systems
Face recognition using Zernike and complex Zernike moment features
Pattern Recognition and Image Analysis
Content-based facial image retrieval using constrained independent component analysis
Information Sciences: an International Journal
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In this paper, we propose two complete sets of similarity invariant descriptors under the Fourier-Mellin transform and the analytical Fourier-Mellin transform (AFMT) frameworks, respectively. The magnitude and phase spectra are jointly processed in our case, and the presented invariants are complete and can be used to reconstruct the image. Their numerical properties are also revealed through image reconstruction. In order to simplify the invariant feature data for recognition and discrimination, a 2D-PCA approach is incorporated into the presented complete invariant descriptor. The obtained compact representation through the 2D-PCA preserves the essential structure of the objects in an image. We tested this compact form on the ORL, Yale and BioID face databases for experimental verification, and achieved a face verification under similarity transforms with a much inferior equal error rate (EER) compared to when the 2D-PCA-based compact form is used without complete invariants.