Yazar "Gorgunoglu, S." seçeneğine göre listele

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    A comparison of minutia triplet based features for fingerprint indexing
    (Institute of Electrical and Electronics Engineers Inc., 2016) Uysal, M.; Gorgunoglu, S.
    The sensitivities of features extracted from minutia triplets, in fingerprint indexing studies, against distortions on impression images have been compared. It has been shown that the geometric features of triangles can be made robust against elastic distortions and features used in other studies called minutia type, ridge counts and ridge pattern representation decrease indexing performance. © 2016 IEEE.
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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.
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    Ridge Pattern Representation for Fingerprint Indexing
    (Kaunas Univ Technology, 2014) Uysal, M.; Gorgunoglu, S.
    Fingerprint is a widely used distinguishing biometric characteristic and indexing has an important role in fingerprint identification for large databases. A method to represent ridge pattern is proposed for fingerprint indexing. Ridge pattern within a triangular area is represented by a numerical value, which is suitable to use as an index and very robust to elastic distortion. Experimental results are promising. The proposed representation method can be utilized to further narrow down the search space of databases by the other indexing methods, especially the ones based on minutiae triplets.
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    Using PCA algorithm in voice recognition
    (2012) Gorgunoglu, S.; Ozkaynak, E.; Orak, I.M.
    Voice is a biometric feature that is used to distinguish or to identify human beings or species. Origin of the existing voice can be determined by analyzing the sound signal. Since voice of the human beings has disparities, it can be used for recognizing people. Various devices or machines are also controlled by voice commands obtained from the words out of the sound signal from one's speeches. In this study, Principal Component Analysis (PCA) algorithm which is mostly used in face recognition system is investigated for voice recognition purposes. PCA algorithm along with Support Vector Machines (SVMs) and K-means algorithms are realized for voice recognition and also their performances are compared. It is shown that PCA algorithm can be used as alternative to the well known voice recognition algorithms © Sila Science.