The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

Raul Sanchezreillo - One of the best experts on this subject based on the ideXlab platform.

  • two different approaches for iris recognition using gabor filters and multiscale zero crossing representation
    Pattern Recognition, 2005
    Co-Authors: Carmen Sanchezavila, Raul Sanchezreillo
    Abstract:

    Abstract Importance of biometric user identification is increasing everyday. One of the most promising techniques is the one based on the human iris. The authors, in this work, describe different approaches to develop this biometric technique. Based on the works carried out by Daugman, the authors have worked using Gabor filters and Hamming distance. But in addition, they have also worked in zero-crossing representation of the dyadic wavelet transform applied to two different iris signatures: one based on a single virtual circle of the iris; the other one based on an annular region. Also other metrics have been applied to be compared with the results obtained with the Hamming distance. In this work Euclidean distance and d Z will be shown. The last proposed approach is translation, rotation and scale invariant. Results will show a classification success up to 99.6% achieving an equal error rate down to 0.12 % and the possibility of having null False acceptance rates with very low False Rejection rates.

  • two different approaches for iris recognition using gabor filters and multiscale zero crossing representation
    Pattern Recognition, 2005
    Co-Authors: Carmen Sanchezavila, Raul Sanchezreillo
    Abstract:

    Abstract Importance of biometric user identification is increasing everyday. One of the most promising techniques is the one based on the human iris. The authors, in this work, describe different approaches to develop this biometric technique. Based on the works carried out by Daugman, the authors have worked using Gabor filters and Hamming distance. But in addition, they have also worked in zero-crossing representation of the dyadic wavelet transform applied to two different iris signatures: one based on a single virtual circle of the iris; the other one based on an annular region. Also other metrics have been applied to be compared with the results obtained with the Hamming distance. In this work Euclidean distance and d Z will be shown. The last proposed approach is translation, rotation and scale invariant. Results will show a classification success up to 99.6% achieving an equal error rate down to 0.12 % and the possibility of having null False acceptance rates with very low False Rejection rates.

  • iris recognition for biometric identification using dyadic wavelet transform zero crossing
    International Carnahan Conference on Security Technology, 2001
    Co-Authors: D De Martinroche, Carmen Sanchezavila, Raul Sanchezreillo
    Abstract:

    A novel biometric identification approach based on the human iris pattern is proposed. The main idea of this technique is to represent the features of the iris by fine-to-coarse approximations at different resolution levels based on the discrete dyadic wavelet transform zero-crossing representation. The resulting one-dimensional (1D) signals are compared with model features using different distances. Before performing the feature extraction, a pre-processing step is to be made by image processing techniques, isolating the iris and enhancing the area of study. The proposed technique is translation, rotation and scale invariant. Results show a classification success above 98%, achieving an equal error rate equal to 0.21% and the possibility of having null False acceptance rates with low False Rejection rates.

Afzel Noore - One of the best experts on this subject based on the ideXlab platform.

  • improving iris recognition performance using segmentation quality enhancement match score fusion and indexing
    Systems Man and Cybernetics, 2008
    Co-Authors: Mayank Vatsa, Richa Singh, Afzel Noore
    Abstract:

    This paper proposes algorithms for iris segmentation, quality enhancement, match score fusion, and indexing to improve both the accuracy and the speed of iris recognition. A curve evolution approach is proposed to effectively segment a nonideal iris image using the modified Mumford-Shah functional. Different enhancement algorithms are concurrently applied on the segmented iris image to produce multiple enhanced versions of the iris image. A support-vector-machine-based learning algorithm selects locally enhanced regions from each globally enhanced image and combines these good-quality regions to create a single high-quality iris image. Two distinct features are extracted from the high-quality iris image. The global textural feature is extracted using the 1-D log polar Gabor transform, and the local topological feature is extracted using Euler numbers. An intelligent fusion algorithm combines the textural and topological matching scores to further improve the iris recognition performance and reduce the False Rejection rate, whereas an indexing algorithm enables fast and accurate iris identification. The verification and identification performance of the proposed algorithms is validated and compared with other algorithms using the CASIA Version 3, ICE 2005, and UBIRIS iris databases.

  • reducing the False Rejection rate of iris recognition using textural and topological features
    World Academy of Science Engineering and Technology International Journal of Computer Electrical Automation Control and Information Engineering, 2008
    Co-Authors: Mayank Vatsa, Richa Singh, Afzel Noore
    Abstract:

    This paper presents a novel iris recognition system using 1D log polar Gabor wavelet and Euler numbers. 1D log polar Gabor wavelet is used to extract the textural features, and Euler numbers are used to extract topological features of the iris. The proposed decision strategy uses these features to authenticate an individual's identity while maintaining a low False Rejection rate. The algorithm was tested on CASIA iris image database and found to perform better than existing approaches with an overall accuracy of 99.93%. MONG the present biometric traits, iris is found to be the most reliable and accurate (1). The use of human iris as a biometric feature offers many advantages over other biometric features. Iris is the internal human body organ that is visible from outside, but well protected from external modifiers. It has epigenetic formation and it is formed from the individual DNA, but a large part of its final pattern is developed at random. Two eyes from the same individual, although are very similar, contain unique patterns. Similarly, identical twins would exhibit four different iris patterns. These characteristics make it attractive for use as a biometric feature to identify individuals. Pattern recognition and image processing algorithms can be used to extract the unique patterns of iris from an eye image and encode it into an iris template. This iris template contains mathematical representation of the unique information stored in the iris and allows comparisons to be made between templates. Since 1990s, many researchers have worked on this problem. Human iris recognition process is basically divided into four steps, • Localization: Inner and outer boundaries of the iris are extracted.

Curtis A Parvin - One of the best experts on this subject based on the ideXlab platform.

  • estimating the performance characteristics of quality control procedures when error persists until detection
    Clinical Chemistry, 1991
    Co-Authors: Curtis A Parvin
    Abstract:

    The concepts of the power function for a quality-control rule, the error detection rate, and the False Rejection rate were major advances in evaluating the performance characteristics of quality-control procedures. Most early articles published in this area evaluated the performance characteristics of quality-control rules with the assumption that an intermittent error condition occurred only within the current run, as opposed to a persistent error that continued until detection. Difficulties occur when current simulation methods are applied to the persistent error case. Here, I examine these difficulties and propose an alternative method that handles persistent error conditions effectively when evaluating and quantifying the performance characteristics of a quality-control rule.

Xuedong Huang - One of the best experts on this subject based on the ideXlab platform.

  • vocabulary independent word confidence measure using subword features
    Conference of the International Speech Communication Association, 1998
    Co-Authors: Li Jiang, Xuedong Huang
    Abstract:

    This paper discusses how to compute word-level confidence measures based on sub-word features for large-vocabulary speaker-independent speech recognition. The performance of confidence measure using features at word, phone and senone level is experimentally studied. A framework of transformation function based system using sub-word features is proposed for high performance confidence estimation. In this system, discriminative training is used to optimize the parameters of the transformation function. In comparison to the baseline, experiments show that the proposed system reduces the equal error rate by 15%, with up to 40% False acceptance error reduction at various fixed False Rejection rate. The combination of multiple features under the proposed framework is also discussed.

James O Westgard - One of the best experts on this subject based on the ideXlab platform.

  • establishing evidence based statistical quality control practices
    American Journal of Clinical Pathology, 2019
    Co-Authors: James O Westgard, Sten A Westgard
    Abstract:

    OBJECTIVES: To establish an objective, scientific, evidence-based process for planning statistical quality control (SQC) procedures based on quality required for a test, precision and bias observed for a measurement procedure, probabilities of error detection and False Rejection for different control rules and numbers of control measurements, and frequency of QC events (or run size) to minimize patient risk. METHODS: A Sigma-Metric Run Size Nomogram and Power Function Graphs have been used to guide the selection of control rules, numbers of control measurements, and frequency of QC events (or patient run size). RESULTS: A tabular summary is provided by a Sigma-Metric Run Size Matrix, with a graphical summary of Westgard Sigma Rules with Run Sizes. CONCLUSION: Medical laboratories can plan evidence-based SQC practices using simple tools that relate the Sigma-Metric of a testing process to the control rules, number of control measurements, and run size (or frequency of QC events).

  • relationship of quality goals and measurement performance to the selection of quality control procedures for multi channel haematology analysers
    European Journal of Haematology, 2009
    Co-Authors: James O Westgard, George S Cembrowski
    Abstract:

    :  An approach is described for selecting QC procedures based on goals for analytical quality, the performance characteristics of the measurement procedure (imprecision, bias, frequency of errors), and the performance characteristics of the control procedure (probabilities for error detection and False Rejection). Performance characteristics of stable sample QC procedures and patient data QC procedures (retained patient specimens, Bull's single-rule algorithm, Bull's multi-rule algorithm) are compared to determine when to apply these different QC procedures to multichannel hematology ! analysers. Precise, stable methods may be controlled using Bull's single-rule algorithm; less precise, less stable methods require Bull's multi-rule algorithm, retained patient specimens, or stable sample QC procedures; imprecise and unstable methods are best controlled using stable sample QC procedures. “Multi-stage” designs may employ stable samples for “startup” testing, retained patient specimens for short term monitoring, and Bull's single-rule algorithm for long term monitoring.