Development of Robust Iris Localization and Impairment Pruning Schemes

Sambit Bakshi

ISBN 10: 3846507695 / ISBN 13: 9783846507698

Published by LAP LAMBERT Academic Publishing Sep 2011, 2011

About this Item

Neuware -Iris is the sphincter having flowery pattern around pupil in eye. The high randomness of the pattern makes iris unique for each individual, and hence a candidate for machine recognition of identity of an individual. The first part of the thesis investigates the bottlenecks of the existing localization approaches and proposes a morphological method of devising an adaptive binarization threshold for pupil detection, and also contributes in modifying conventional integrodifferential operator based iris detection using canny detected edge map. The review of related works on matching leads to the observation that local features like Scale Invariant Feature Transform(SIFT) matches the keypoints on the basis of 128-D local descriptors, hence it sometimes falsely pairs two keypoints which are from different portions of two iris images. Subsequently the need for pruning of faulty SIFT pairs is felt. The second part of the thesis proposes two methods of filtering (Angular Filtering and Scale Filtering) the SIFT impairments (faulty pairs) based on the knowledge of spatial information of the keypoints. The pruning algorithms experimentally show higher accuracy and increased separability.Books on Demand GmbH, Überseering 33, 22297 Hamburg 76 pp. Englisch.

Seller Inventory # 9783846507698

Bibliographic Details

• Title: Development of Robust Iris Localization and Impairment Pruning Schemes
• Publisher: LAP LAMBERT Academic Publishing Sep 2011
• Publication Date: 2011
• Language: English
• ISBN 10: 3846507695
• ISBN 13: 9783846507698
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

Iris is the sphincter having flowery pattern around pupil in eye. The high randomness of the pattern makes iris unique for each individual, and hence a candidate for machine recognition of identity of an individual. The first part of the thesis investigates the bottlenecks of the existing localization approaches and proposes a morphological method of devising an adaptive binarization threshold for pupil detection, and also contributes in modifying conventional integrodifferential operator based iris detection using canny detected edge map. The review of related works on matching leads to the observation that local features like Scale Invariant Feature Transform(SIFT) matches the keypoints on the basis of 128-D local descriptors, hence it sometimes falsely pairs two keypoints which are from different portions of two iris images. Subsequently the need for pruning of faulty SIFT pairs is felt. The second part of the thesis proposes two methods of filtering (Angular Filtering and Scale Filtering) the SIFT impairments (faulty pairs) based on the knowledge of spatial information of the keypoints. The pruning algorithms experimentally show higher accuracy and increased separability.

About the Author

Sambit Bakshi is presently a Ph.D. scholar working on emerging trends of biometric systems. His research interests include Image Processing, Computer Vision and Pattern Recognition. The work presented in this book is awarded Innovative Student Projects Award – 2011 (Master’s Level) by Indian National Academy of Engineering (INAE).