Dalgacık dönüşümü kullanarak videoda insan yüzü ve gözlerin yerlerinin tespiti

Human face detection and eye localization problems have received significantattention during the past several years because of wide range of commercial andlaw enforcement applications. In this thesis, wavelet domain based human facedetection and eye localization algorithms are developed. After determining allpossible face candidate regions using color information in a given still image orvideo frame, each region is filtered by a high-pass filter of a wavelet transform.In this way, edge-highlighted caricature-like representations of candidate regionsare obtained. Horizontal, vertical and filter-like edge projections of the candi-date regions are used as feature signals for classification with dynamic program-ming (DP) and support vector machines (SVMs). It turns out that the proposedfeature extraction method provides good detection rates with SVM based clas-sifiers. Furthermore, the positions of eyes can be localized successfully usinghorizontal projections and profiles of horizontal- and vertical-crop edge image re-gions. After an approximate horizontal level detection, each eye is first localizedhorizontally using horizontal projections of associated edge regions. Horizontaledge profiles are then calculated on the estimated horizontal levels. After deter-mining eye candidate points by pairing up the local maximum point locationsin the horizontal profiles with the associated horizontal levels, the verification isalso carried out by an SVM based classifier. The localization results show thatthe proposed algorithm is not affected by both illumination and scale changes.iiiivKeywords: Human face detection, eye detection, eye localization, wavelet trans-form, edge projections, classification, support vector machines, dynamic program-ming.