Fundamentals of digital image processing
Fundamentals of digital image processing
Characterization of Signals from Multiscale Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised texture segmentation using Gabor filters
Pattern Recognition
Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Iris Recognition with Low Template Size
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Personal Identification Based on Iris Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Biometric Systems: Technology, Design and Performance Evaluation
Biometric Systems: Technology, Design and Performance Evaluation
Iris verification using correlation filters
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Iris feature extraction using independent component analysis
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
A human identification technique using images of the iris andwavelet transform
IEEE Transactions on Signal Processing
Verification of computer users using keystroke dynamics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
The multicomponent AM-FM image representation
IEEE Transactions on Image Processing
Efficient iris recognition by characterizing key local variations
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
A Survey on Statistical Pattern Feature Extraction
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
A Robust Iris Localization Model Based on Phase Congruency and Least Trimmed Squares Estimation
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
A novel iris segmentation using radial-suppression edge detection
Signal Processing
Car plate recognition by whole 2-D image
Expert Systems with Applications: An International Journal
Proceedings of the International Conference & Workshop on Emerging Trends in Technology
Iris recognition failure over time: The effects of texture
Pattern Recognition
A simple boundary extraction technique for irregular pupil localization with orthogonal polynomials
Computer Vision and Image Understanding
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The randomness of iris pattern makes it one of the most reliable biometric traits. On the other hand, the complex iris image structure and the various sources of intra-class variations result in the difficulty of iris representation. Although, a number of iris recognition methods have been proposed, it has been found that several accurate iris recognition algorithms use multiscale techniques, which provide a well-suited representation for iris recognition. In this paper and after a thorough analysis and summarization, a multiscale edge detection approach has been employed as a pre-processing step to efficiently localize the iris followed by a new feature extraction technique which is based on a combination of some multiscale feature extraction techniques. This combination uses special Gabor filters and wavelet maxima components. Finally, a promising feature vector representation using moment invariants is proposed. This has resulted in a compact and efficient feature vector. In addition, a fast matching scheme based on exclusive OR operation to compute bits similarity is proposed where the result experimentation was carryout out using CASIA database. The experimental results have shown that the proposed system yields attractive performances and could be used for personal identification in an efficient and effective manner and comparable to the best iris recognition algorithm found in the current literature.