Yazar "Orak, I. Muharrem" seçeneğine göre listele

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    Electrooculogram and Diplopia Controlled Fuzzy Direction Detect System
    (Ieee, 2014) Erkaymaz, Hande; Orak, I. Muharrem; Ozer, Mahmut
    Coding of the organ movements have been seen commonly in the hardware designing which is useful for humanity in scientific researches. 5 sense organs which reveal different data with cellular structures, is the most important focus point. Especially, Eye is known as photosensitive sensor organ of living creature. There is a potential difference between cornea and retina of eye. This potential difference is known as electrooculogram (FOG). Nowadays, FOG signals are commonly used in these hardware designs. Obtained potential differences from FOG signals have been converted coded directional movements. Thus, in this study, 4 basic direction movements have been tried to detect with a fuzzy controlled model. It is shown that the fuzzy controlled system as determine the direction can be used successfully. In addition, eye direction movements of squint person are obtained by the system.
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    EOG Based Intelligent Direction Detect System with Pre-Filtering Algorithm
    (Ieee, 2015) Erkaymaz, Hande; Ozer, Mahmut; Kaya, Ceren; Orak, I. Muharrem
    Nowadays, artificial movements have been obtained by utilizing other organs for paralyzed patients. Especially the usage of eye movements for giving message to outside world became popular as a scientific subject. In studies according to eye movements, the Electrooculogram (EOG) signal is used. In this study, the vertical and horizontal FOG signals taken from electrodes, placed around the eyes, have been modelled by using Artificial Neural Networks (ANN) which is one of artificial intelligent technique. The system can sense four main directions (Right, Left, Up and Down) at the same time it can also detect blinking movements. Firstly, the signals have been pre-filtered, amplified and classified by ANN. The performance of recommended model has been demonstrated by analyzing statistical accuracy and confusion matrix according to the features of obtained signal. It has been seen that eye movements can be successfully determined by designed model.
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    Fingerprint Pre-processing on ARM and DSP Platforms
    (Kaunas Univ Technology, 2014) Gok, M.; Gorgunoglu, S.; Orak, I. Muharrem
    In minutiae based fingerprint analysis, fingerprint image is pre-processed before extracting features. The pre-processing is carried out to obtain more accurate minutiae points. Implementing fingerprint programs on embedded systems can be considered as important especially for real time standalone applications. Reducing the preprocessing time is important for identification and verification in real time embedded systems. In this study, pre-processing of minutiae based fingerprint system is implemented on two different platforms: Texas Instruments Sitara AM3359 which is a single board computer and OMAP-L138 which is a development kit. OMAP-L138 is a low power application processor based on ARM9 and C674x DSP cores. AM3359 is microprocessor unit based on ARM Cortex-A8 core. Fingerprint pre-processing algorithms are implemented using C/C++ compiler and tested on three different cores: ARM9, DSP and ARM Cortex-A8. The execution times are compared with each other. The results show that using DSP core, execution time is substantially improved.