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http://hdl.handle.net/10603/490159
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DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | IRIS Recognition | |
dc.date.accessioned | 2023-06-08T09:04:51Z | - |
dc.date.available | 2023-06-08T09:04:51Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/490159 | - |
dc.description.abstract | Biometrics is trust-worthy and automatic recognition process which maps distinctive characteristics of an individual. Biometrics identifiers mainly use for realistic authentication and access control. Biometrics categorized in physiological and behavioral characteristics. In physiological characteristics which are related to body shapes. Examples of these characteristics are face, palm print, hand geometry, iris, fingerprint, DNA. Examples of behavioral characteristics are typing rhythm, gait and voice. Among these iris has described as ideal part of human body because iris is mainly protected internal organ of eye and it has random pattern of great complexity which has uniqueness. Iris pattern is always constant throughout life. Reliable personal identification using iris as a biometric is recently an active topic in the research area of pattern recognition. It is because of increase in the demand of enhanced security of human being in daily life. Automated iris recognition is yet another alternative for non-invasive verification and identification of people. Even though newlineDaugman [1-5] proved greatest accuracy using iris based human identification system, there is still problem with partial and important iris region selection for recognition of partially occluded iris images. Also there is need development of own iris image acquisition set up to acquire clear iris images to propose huge iris image database. Hence to overcome problem of partial and important iris region selection for recognition of partially occluded iris image due to lower eyelids, firstly we have implemented iris recognition algorithm using cumulative sums based change analysis by proposed partial iris from lower half part of the iris leaving 8 inner pixels from outer boundary of iris. Fuzzy hamming distance classifier is proposed as best classifier as compared to hamming distance classifier for the iris recognition using cumulative sums based change analysis. DCT based iris recognition algorithm have been implemented for the same proposed iris | |
dc.format.extent | 76p | |
dc.language | English | |
dc.relation | 86b | |
dc.rights | university | |
dc.title | IRIS Recognition for Personal Identification using Texture Based Analysis | |
dc.title.alternative | ||
dc.creator.researcher | Kamble, Usha Ramdas | |
dc.subject.keyword | Engineering | |
dc.subject.keyword | Engineering and Technology | |
dc.subject.keyword | Engineering Electrical and Electronic | |
dc.description.note | ||
dc.contributor.guide | Waghmare L. M. | |
dc.publisher.place | Nanded | |
dc.publisher.university | Swami Ramanand Teerth Marathwada University | |
dc.publisher.institution | Department of Electronics and Telecommunication Engineering | |
dc.date.registered | 2008 | |
dc.date.completed | 2021 | |
dc.date.awarded | 2021 | |
dc.format.dimensions | ||
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Department of Electronics and Telecommunication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 66.29 kB | Adobe PDF | View/Open |
02_certificate.pdf | 365.81 kB | Adobe PDF | View/Open | |
03_abstract.pdf | 60.37 kB | Adobe PDF | View/Open | |
04_decleration.pdf | 48.5 kB | Adobe PDF | View/Open | |
05_acknowledgement.pdf | 63.85 kB | Adobe PDF | View/Open | |
06_contents.pdf | 442.36 kB | Adobe PDF | View/Open | |
07_list of tables.pdf | 42.99 kB | Adobe PDF | View/Open | |
08_list of figures.pdf | 39.76 kB | Adobe PDF | View/Open | |
09_abbreviations.pdf | 277.56 kB | Adobe PDF | View/Open | |
10_chapter 1.pdf | 921.51 kB | Adobe PDF | View/Open | |
11_chapter 2.pdf | 1.21 MB | Adobe PDF | View/Open | |
12_chapter 3.pdf | 595.29 kB | Adobe PDF | View/Open | |
13_chapter 4.pdf | 933.35 kB | Adobe PDF | View/Open | |
14_chapter 5.pdf | 728.26 kB | Adobe PDF | View/Open | |
15_conclusions.pdf | 215.93 kB | Adobe PDF | View/Open | |
16_summary.pdf | 224.47 kB | Adobe PDF | View/Open | |
17_bibliography.pdf | 371.86 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 499 kB | Adobe PDF | View/Open |
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