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Recognition Approach (recognition + approach)

Distribution by Scientific Domains

Medical Sciences	50%
Engineering	50%

Selected Abstracts

An iris recognition approach through structural pattern analysis methods

EXPERT SYSTEMS, Issue 1 2010
Hugo Proença
Abstract: Continuous efforts have been made to improve the robustness of iris coding methods since Daugman's pioneering work on iris recognition was published. Iris recognition is at present used in several scenarios (airport check-in, refugee control etc.) with very satisfactory results. However, in order to achieve acceptable error rates several imaging constraints are enforced, which reduce the fluidity of the iris recognition systems. The majority of the published iris recognition methods follow a statistical pattern recognition paradigm and encode the iris texture information through phase, zero-crossing or texture-analysis based methods. In this paper we propose a method that follows the structural (syntactic) pattern recognition paradigm. In addition to the intrinsic advantages of this type of approach (intuitive description and human perception of the system functioning), our experiments show that the proposed method behaves comparably to the statistical approach that constitutes the basis of nearly all deployed systems. [source]

Color invariant object recognition using entropic graphs

INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, Issue 5 2006
Jan C. van Gemert
Abstract We present an object recognition approach using higher-order color invariant features with an entropy-based similarity measure. Entropic graphs offer an unparameterized alternative to common entropy estimation techniques, such as a histogram or assuming a probability distribution. An entropic graph estimates entropy from a spanning graph structure of sample data. We extract color invariant features from object images invariant to illumination changes in intensity, viewpoint, and shading. The Henze,Penrose similarity measure is used to estimate the similarity of two images. Our method is evaluated on the ALOI collection, a large collection of object images. This object image collection consists of 1000 objects recorded under various imaging circumstances. The proposed method is shown to be effective under a wide variety of imaging conditions. © 2007 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 16, 146,153, 2006 [source]

Comparison of two new approaches to variable ordering for binary decision diagrams

QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 3 2001
L. M. Bartlett
Abstract Fault tree analysis, FTA, is one of the most commonly used techniques for safety system analysis. There can be problems with the efficiency and accuracy of the approach when dealing with large tree structures. Recently the binary decision diagram (BDD) methodology has been introduced which significantly aids the analysis of the fault tree diagram. The approach has been shown to improve both the efficiency of determining the minimal cut sets of the fault tree, and also the accuracy of the calculation procedure used to quantify the top event parameters. To utilize the BDD technique the fault tree structure needs to be converted into the BDD format. Converting the fault tree is relatively straightforward but requires the basic events of the tree to be placed in an ordering. The ordering of the basic events is critical to the resulting size of the BDD, and ultimately affects the performance and benefits of this technique. There are a number of variable ordering heuristics in the literature, however the performance of each depends on the tree structure being analysed. These heuristic approaches do not yield a minimal BDD structure for all trees, some approaches generate orderings that are better for some trees but worse for others. Within this paper two approaches to the variable ordering problem have been discussed. The first is the pattern recognition approach of neural networks, which is used to select the best ordering heuristic for a given fault tree from a set of alternatives. The second examines a completely new heuristic approach of using the structural importance of a component to produce a ranked ordering. The merits of each are discussed and the results compared. Copyright © 2001 John Wiley & Sons, Ltd. [source]

Recent advances in T-cell regulation relevant to inflammatory dermatopathology

JOURNAL OF CUTANEOUS PATHOLOGY, Issue 7 2009
Laszlo J. Karai
Inflammatory dermatoses encompass an enormous area of dermatopathology. Our understanding of the subject comes from combination of histopathological observations and relevant clinical information. Diagnoses are generally reached at the hematoxylin and eosin (H&E) level by using various pattern recognition approaches including one devised by Dr Ackerman et al.1 Recent advances in cell biology and immunology especially the field of T-cell regulation shed light to the intricate cellular interactions, associations and connect to inflammatory dermatopathology. This review attempts to identify and put into context the most significant advances in cellular biology relevant to the topic. Most of the information presented here is not necessarily relevant to our regular work at the moment; however, the new information will surely channel into our practice to provide a better, more accurate, semi-individualized diagnostic approach in the not too far future. [source]