Author Type

Graduate Student

Date of Award

2011

Document Type

Thesis

Publication Status

Version of Record

Submission Date

October 2026

Abstract

The efforts addressed in this thesis refer to assaying the extent of local features in 2D-images for the purpose of recognition and classification. It is based on comparing a test-image against a template in binary format. It is a bioinformatics-inspired approach pursued and presented as deliverables of this thesis as summarized below: 1. By applying the so-called 'Smith-Waterman (SW) local alignment' and 'Needleman-Wunsch (NW) global alignment' approaches of bioinformatics, a test 2D-image in binary format is compared against a reference image so as to recognize the differential features that reside locally in the images being compared 2. SW and NW algorithms based binary comparison involves conversion of one-dimensional sequence alignment procedure (indicated traditionally for molecular sequence comparison adopted in bioinformatics) to 2D-image matrix 3. Relevant algorithms specific to computations are implemented as MatLabTM codes 4. Test-images considered are: Real-world bio-/medical-images, synthetic images, microarrays, biometric finger prints (thumb-impressions) and handwritten signatures. Based on the results, conclusions are enumerated and inferences are made with directions for future studies.

Extent

xii, 122 p. : ill. (some col.)

Comments

by Deepti Pappusetty.|Thesis (M.S.C.S.)--Florida Atlantic University, 2011.|Includes bibliography.|Electronic reproduction. Boca Raton, Fla., 2011. Mode of access: World Wide Web.|by Deepti Pappusetty.

Identifier

FADT3333052

Format

pdf

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