Face segmentation in thermal images

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Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümü, Türkiye

Tezin Onay Tarihi: 2015

Öğrenci: MELİS ERYILMAZ

Danışman: GÖZDE AKAR

Özet:

Automatic face segmentation is a key issue in many applications such as machine vision, coding, etc. Therefore, the accuracy of the segmentation algorithms results has a strong impact on the later stages. These algorithms should also be computationally efficient and robust against changing environments. The aim of this thesis is to analyze different approaches for face segmentation and compare them in terms of the robustness and computational efficiency. Four different face segmentation methods are chosen to be compared in the scope of this thesis. Experiments are performed on IRIS and Terravic databases. Implemented face segmentation methods are compared according to their classification performances and error rates.