Spelling suggestions: "subject:"attern perception -- data processing"" "subject:"attern perception -- mata processing""
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Bioinformatics-inspired binary image correlation: application to bio-/medical-images, microsarrays, finger-prints and signature classificationsUnknown Date (has links)
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. / 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.
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GrailKnights : an automaton mass manipulation package for enhanced pattern analysisDu Preez, Hercule 03 1900 (has links)
Thesis (MSC (Mathematical Sciences. Computer Science))--Stellenbosch University, 2008. / This thesis describes the design and implementation of an application names GrailKnights that allows for the mass manipulation of automata, with added visual pattern analysis features. It comprises a database-driven backend for automata storage, and a graphical user interface that allows for filtering the automata selected from the database with visual interpretation of visible patterns over the resulting automata.
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