On the Use of SDF-Type Filters for Distortion Parameter Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of RST invariant image watermarking algorithms
ACM Computing Surveys (CSUR)
Iris verification using correlation filters
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
An evaluation of video-to-video face verification
IEEE Transactions on Information Forensics and Security
Principal directions of synthetic exact filters for robust real-time eye localization
BioID'11 Proceedings of the COST 2101 European conference on Biometrics and ID management
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part II
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Correlation methods are becoming increasingly attractive tools for image recognition and location. This renewed interest in correlation methods is spurred by the availability of high-speed image processors and the emergence of correlation filter designs that can optimize relevant figures of merit. In this paper, a new correlation filter design method is presented that allows one to optimally tradeoff among potentially conflicting correlation output performance criteria while achieving desired correlation peak value behavior in response to in-plane rotation of input images. Such controlled in-plane rotation response is useful in image analysis and pattern recognition applications where the sensor follows a pre-arranged trajectory while imaging an object. Since this new correlation filter design is based on circular harmonic function (CHF) theory, we refer to the resulting filters as optimal tradeoff circular harmonic function (OTCHF) filters. Underlying theory, OTCHF filter design method, and illustrative numerical results are presented