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Automatic feature extraction for pattern recognition / by Jamie Sherrah.Sherrah, Jamie January 1998 (has links)
CD-ROM in back pocket comprises experimental results and executables. / System requirements: Unix workstation or PC with Windows 95 or Windows NT. The reports output by EPrep. can be viewed with a web browser such as Netscape or Microsoft Internet Explorer through the top level HTML page. / Bibliography: p. 251-261. / Computer data and programs / HTML reports, data and figures generated by EPrep / xxiv, 261 p. : ill. ; 30 cm. + 1 computer laser optical disk ; 4 3/4". / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Proposes a framework for automatic feature extraction called generalised pre-processor. / Thesis (Ph.D.)--University of Adelaide, Dept. of Electrical and Electronic Engineering, 1999
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Automatic feature extraction for pattern recognition / by Jamie Sherrah.Sherrah, Jamie January 1998 (has links)
CD-ROM in back pocket comprises experimental results and executables. / System requirements: Unix workstation or PC with Windows 95 or Windows NT. The reports output by EPrep. can be viewed with a web browser such as Netscape or Microsoft Internet Explorer through the top level HTML page. / Bibliography: p. 251-261. / Computer data and programs / HTML reports, data and figures generated by EPrep / xxiv, 261 p. : ill. ; 30 cm. + 1 computer laser optical disk ; 4 3/4". / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Proposes a framework for automatic feature extraction called generalised pre-processor. / Thesis (Ph.D.)--University of Adelaide, Dept. of Electrical and Electronic Engineering, 1999
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Using synthetic images to improve iris biometric performanceHasegawa, Robert Shigehisa 01 January 2012 (has links) (PDF)
The rapid advance of information technology has allowed for a rise in the use of biometric markers to automatically track the identity of individuals. Iris biometrics has emerged as one of the most reliable and accurate systems when dealing with cooperating subjects, however, challenges arise when attempting to minimize the amount of intrusion when examining subjects. Allowing for more flexibility in data capture settings will introduce differences in the iris texture due to changes in ambient light, which may negatively impact recognition results. This research examines the feasibility of using 3D software to synthetically dilate the pupils of existing iris images to more closely match the size of a target image. Methods are developed first to evaluate the compatibility of synthetic images with iris identification software, and then to examine what specific areas of the iris texture differ between synthetic and real images. Results show synthetic images are found to be compatible with the recognition process and have the potential to improve performance.
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