Face segmentation in thermal images /

Eryılmaz, Melis
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.


Moving hot object detection in airborne thermal videos
Kaba, Utku; Akar, Gözde; Department of Electrical and Electronics Engineering (2012)
In this thesis, we present an algorithm for vision based detection of moving objects observed by IR sensors on a moving platform. In addition we analyze the performance of different approaches in each step of the algorithm. The proposed algorithm is composed of preprocessing, feature detection, feature matching, homography estimation and difference image analysis steps. First, a global motion estimation based on planar homography model is performed in order to compensate the motion of the sensor and moving ...
Object recognition and segmentation via shape models
Altınoklu, Metin Burak; Ulusoy, İlkay; Tarı, Zehra Sibel; Department of Electrical and Electronics Engineering (2016)
In this thesis, the problem of object detection, recognition and segmentation in computer vision is addressed with shape based methods. An efficient object detection method based on a sparse skeleton has been proposed. The proposed method is an improved chamfer template matching method for recognition of articulated objects. Using a probabilistic graphical model structure, shape variation is represented in a skeletal shape model, where nodes correspond to parts consisting of lines and edges correspond to pa...
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Çiftçi, Serdar; Yarman Vural, Fatoş Tunay; Kalkan, Sinan; Department of Computer Engineering (2011)
Edge detection is an important step in computer vision since edges are utilized by the successor visual processing stages including many tasks such as motion estimation, stereopsis, shape representation and matching, etc. In this study, we test whether a local consistency measure based on image orientation (which we call Intersection Consistency - IC), which was previously shown to improve detection of junctions, can be used for improving the quality of edge detection of seven different detectors; namely, C...
Edge strength functions as shape priors in image segmentation
Erdem, Erkut; Erdem, Aykut; Tarı, Zehra Sibel (2005-12-01)
Many applications of computer vision requires segmenting out of an object of interest from a given image. Motivated by unlevel-sets formulation of Raviv, Kiryati and Sochen [8] and statistical formulation of Leventon, Grimson and Faugeras [6], we present a new image segmentation method which accounts for prior shape information. Our method depends on Ambrosio-Tortorelli approximation of Mumford-Shah functional. The prior shape is represented by a by-product of this functional, a smooth edge indicator functi...
Low--‐cost uncooled infrared imaging sensor using mems and a modified standard cmos process
Gülden, Mehmet Ali; Akın, Tayfun; Eminoğlu, Selim; Department of Electrical and Electronics Engineering (2013)
The thesis presents a monolithically integrated low-­‐cost uncooled infrared imaging sensor using a MEMS process and a modified standard CMOS process. The designed sensor has an image format of 160×120 with a pixel pitch of 40 μm. The sensor is implemented with microbolometers that sense the infrared radiation in the 8-­‐12 μm spectral band, where the sensing elements in each pixel are formed with CMOS diodes to sense the temperature variation in the pixel by monitoring the change in the forward bias voltag...
Citation Formats
M. Eryılmaz, “Face segmentation in thermal images /,” M.S. - Master of Science, Middle East Technical University, 2015.