Face segmentation in thermal images /

Date

2015

Author

Eryılmaz, Melis

Metadata

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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.

Subject Keywords

Infrared imaging., Image processing., Imaging systems., Gaussian distribution.

URI

http://etd.lib.metu.edu.tr/upload/12618501/index.pdf
https://hdl.handle.net/11511/24444

Collections

Graduate School of Natural and Applied Sciences, Thesis