Browsing by Author "Swanepoel, Jacques Philip"

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    Off-line signature verification using classifier ensembles and flexible grid features
    (Stellenbosch : University of Stellenbosch, 2009-12) Swanepoel, Jacques Philip; Coetzer, Johannes; University of Stellenbosch. Faculty of Science. Dept. of Mathematical Sciences.
    ENGLISH ABSTRACT: In this study we investigate the feasibility of combining an ensemble of eight continuous base classifiers for the purpose of off-line signature verification. This work is mainly inspired by the process of cheque authentication within the banking environment. Each base classifier is constructed by utilising a specific local feature, in conjunction with a specific writer-dependent signature modelling technique. The local features considered are pixel density, gravity centre distance, orientation and predominant slant. The modelling techniques considered are dynamic time warping and discrete observation hidden Markov models. In this work we focus on the detection of high quality (skilled) forgeries. Feature extraction is achieved by superimposing a grid with predefined resolution onto a signature image, whereafter a single local feature is extracted from each signature sub-image corresponding to a specific grid cell. After encoding the signature image into a matrix of local features, each column within said matrix represents a feature vector (observation) within a feature set (observation sequence). In this work we propose a novel flexible grid-based feature extraction technique and show that it outperforms existing rigid grid-based techniques. The performance of each continuous classifier is depicted by a receiver operating characteristic (ROC) curve, where each point in ROC-space represents the true positive rate and false positive rate of a threshold-specific discrete classifier. The objective is therefore to develope a combined classifier for which the area-under-curve (AUC) is maximised -or for which the equal error rate (EER) is minimised. Two disjoint data sets, in conjunction with a cross-validation protocol, are used for model optimisation and model evaluation. This protocol avoids possible model overfitting, and also scrutinises the generalisation potential of each classifier. During the first optimisation stage, the grid configuration which maximises proficiency is determined for each base classifier. During the second optimisation stage, the most proficient ensemble of optimised base classifiers is determined for several classifier fusion strategies. During both optimisation stages only the optimisation data set is utilised. During evaluation, each optimal classifier ensemble is combined using a specific fusion strategy, and retrained and tested on the separate evaluation data set. We show that the performance of the optimal combined classifiers is significantly better than that of the optimal individual base classifiers. Both score-based and decision-based fusion strategies are investigated, which includes a novel extension to an existing decision-based fusion strategy. The existing strategy is based on ROC-statistics of the base classifiers and maximum likelihood estimation. We show that the proposed elitist maximum attainable ROC-based strategy outperforms the existing one.
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    Writer-independent handwritten signature verification
    (Stellenbosch : Stellenbosch University, 2015-12) Swanepoel, Jacques Philip; Coetzer, Johannes; Stellenbosch University. Faculty of Science. Department of Mathematical Sciences (Applied Mathematics).
    AFRIKAANSE OPSOMMING : In hierdie verhandeling stel ons 'n nuwe strategie vir outomatiese handtekening-verifikasie voor. Die voorgestelde raamwerk gebruik 'n skrywer-onafhanklike benadering tot handtekening- modellering en is dus in staat om bevraagtekende handtekeninge, wat aan enige skrywer behoort, te bekragtig, op voorwaarde dat minstens een outentieke voorbeeld vir vergelykingsdoeleindes beskikbaar is. Ons ondersoek die tradisionele statiese geval (waarin 'n bestaande pen-op-papier handtekening vanuit 'n versyferde dokument onttrek word), asook die toenemend gewilde dinamiese geval (waarin handtekeningdata outomaties tydens ondertekening m.b.v. gespesialiseerde elektroniese hardeware bekom word). Die statiese kenmerk-onttrekkingstegniek behels die berekening van verskeie diskrete Radontransform (DRT) projeksies, terwyl dinamiese handtekeninge deur verskeie ruimtelike en temporele funksie-kenmerke in die kenmerkruimte voorgestel word. Ten einde skryweronafhanklike handtekening-ontleding te bewerkstellig, word hierdie kenmerkstelle na 'n verskil-gebaseerde voorstelling d.m.v. 'n geskikte digotomie-transformasie omgeskakel. Die klassikasietegnieke, wat vir handtekeking-modellering en -verifikasie gebruik word, sluit kwadratiese diskriminant-analise (KDA) en steunvektormasjiene (SVMe) in. Die hoofbydraes van hierdie studie sluit twee nuwe tegnieke, wat op die bou van 'n robuuste skrywer-onafhanklike handtekeningmodel gerig is, in. Die eerste, 'n dinamiese tydsverbuiging digotomie-transformasie vir statiese handtekening-voorstelling, is in staat om vir redelike intra-klas variasie te kompenseer, deur die DRT-projeksies voor vergelyking nie-lineêr te belyn. Die tweede, 'n skrywer-spesieke verskil-normaliseringstrategie, is in staat om inter-klas skeibaarheid in die verskilruimte te verbeter deur slegs streng relevante statistieke tydens die normalisering van verskil-vektore te beskou. Die normaliseringstrategie is generies van aard in die sin dat dit ewe veel van toepassing op beide statiese en dinamiese handtekening-modelkonstruksie is. Die stelsels wat in hierdie studie ontwikkel is, is spesi ek op die opsporing van hoë-kwaliteit vervalsings gerig. Stelselvaardigheid-afskatting word met behulp van 'n omvattende eksperimentele protokol bewerkstellig. Verskeie groot handtekening-datastelle is oorweeg. In beide die statiese en dinamiese gevalle vaar die voorgestelde SVM-gebaseerde stelsel beter as die voorgestelde KDA-gebaseerde stelsel. Ons toon ook aan dat die stelsels wat in hierdie studie ontwikkel is, die meeste bestaande stelsels wat op dieselfde datastelle ge evalueer is, oortref. Dit is selfs meer belangrik om daarop te let dat, wanneer hierdie stelsels met bestaande tegnieke in die literatuur vergelyk word, ons aantoon dat die gebruik van die nuwe tegnieke, soos in hierdie studie voorgestel, konsekwent tot 'n statisties beduidende verbetering in stelselvaardigheid lei.