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Öğe Detection of stationary aircrafts from satelitte images(2011) Yildiz C.; Polat E.It is one of the common problems to identify objects in satellite images of earth using computer vision and image processing techniques. It is especially important to determine the coordinates of civil and military aircrafts in an airport or anyplace is crucial for military intelligence. In this paper we achieved to identify the aircrafts from airport images taken from a specific altitude using computer vision techniques. For this purpose the images have been searched that previously identified by SVM classifier derived from Google Earth® the aircraft images. Gabor filter is used to refine the features of aircraft and extract the feature vector. SVM has been applied on data that feature extraction made before and determination of aircraft image has been confirmed.Öğe Neuropsychiatric disorders classification using a video based pupil detection system(2012) Akinci G.; Polat E.; Koçak O.M.Eye tracking systems have become increasingly popular in computer vision applications. In this study, a video-based pupil detection system and neuropsychological tests for the system are developed for diagnosing of neuropsychiatric disorders. An Active Contour Snake model with ellipse fitting algorithm is proposed to extract the position (x, y) and radius (r) information of pupils in video sequences. The neuropsychological tests in this research are applied to three different groups, namely; bipolar disorder group, control group and schizophrenia group. In order to conduct the neuropsychological tests, a number of selected words are shown to the people on a computer screen. The pupil detection system is used to determine the duration and the coordinates of the screen where the eye looking at while reading the test words in real time. The information acquired from the tests is used as a feature vector in Support Vector Machines (SVM) for classifying the neuropsychiatric disorder (bipolar) and normal (control) groups. The information acquired from schizophrenia group is also presented for the same tests. © 2012 IEEE.Öğe Stationary aircraft detection from satellite images(Istanbul University, 2012) Polat E.; Yildiz C.Satellite image analysis is an important research area in the field of image processing. Detection and recognition of regions and objects from satellite images find many useful civil applications such as detection of buildings, roads, bridges and other man-made objects as well as land plant classification. On the other hand, the detection of stationary aircrafts in airports can be strategically important in military applications. In this study, a learning-based system that detects stationary aircrafts in satellite images obtained from Google Earth is developed. The features that emphasize the geometric structure of an aircraft are determined using 2D Gabor filter. The aircraft detection is performed using Support Vector Machines (SVM) classification method. The SVM is a supervised learning method that analyzes data and recognizes patterns for classification The SVM takes a set of input data (a vector consists of Gabor filter output of images) and predicts the one of two classes (aircraft or non-aircraft). The performance of the system is demonstrated using satellite images collected from airports in Europe and United States.Öğe A video based eye detection system for bipolar disorder diagnosis(2012) Akinci G.; Polat E.; Koçak O.M.In this study, a video-based pupil detection system and neuropsychological tests for the system are developed for diagnosis of neuropsychiatric disorders. An Active Contour Snake model is proposed to extract the position (x,y) and radius (r) information of pupils in video sequences. The test in this research is applied to two different groups, namely; bipolar disorder group and control (nonbipolar) group. In order to conduct the test application, a number of selected words are shown to the people on a computer screen. While they are reading these words, the pupil detection system is used to determine the coordinates of the screen where the eye looking at and how long it takes to look at these words simultaneously. This information acquired from these tests is used as a feature vector in Support Vector Machines (SVM) for classifying the bipolar disorder and control groups. © 2012 IEEE.
