Browsing by Author "Özdil, Ahmet"

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Automated processing and classification of medical thermal images
(Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2022) Özdil, Ahmet; AGÜ, Fen Bilimleri Enstitüsü, Elektrik ve Bilgisayar Mühendisliği Ana Bilim Dalı
The aim of this dissertation is to develop computer aided methods for processing and evaluating medical infrared thermal images. Throughout this study three problems were evaluated. The first problem was to automatically classify the body part and pose in the thermal images. In this study there were four classes; upper-lower body parts with back-front views. The first step included the segmentation of the background with Otsu’s thresholding method applying histogram equalization. Next, DarkNet-19 architecture was used to extract features from images and these features were reduced using PCA and tSNE methods. Finally reduced feature sets were used for classification. The second problem was to automatically classify liver steatosis from using thermal images. In this study, the classification problem was tested on an anatomical region of interest from abdominal images corresponding to the liver. Deep learning and texture analysis methods were employed for feature extraction, and then the selected feature sets were used for classification. The third problem was to quantify thermograms of multiple sclerosis (MS) patients for better assessment of the disease and monitoring the therapy. Thermal images of two patients and a healthy control from lower limbs were evaluated during experiments, and localized quantification of the effect of MS on the feet of the patients using thermal images method was proposed. The proposed method was fully correlated with the evaluations of physician. It is shown that medical thermal imaging has high potential in many fields of medicine as a non-invasive method for pre-diagnosis and follow-up.
A Survey on Comparison of Face Recognition Algorithms
(IEEE, 2014) Özdil, Ahmet; Ozhilen, Metin Mete; 0000-0002-6651-1968; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Özdil, Ahmet
The identification of a face from a video or image source is a study of computer vision know as face detection or recognition. Face detection and recognition becomes popular in recent years by the development of computing power. In this study we will present performance aspect of algorithms Eigenfaces, Fisherfaces, and Local Binary Pattern Histograms in different development platforms: Arm and Intel processors.