Elektronik ve Haberleşme Mühendisliği Bölümü Yayın Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/260

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Citation Count: Yarkan, S...et al. (2012). An online adaptive cooperation scheme for spectrum sensing based on a second-order statistical method. IEEE Transactions On Vehicular Technology, 61(2), 675-686. http://dx.doi.org/10.1109/TVT.2011.2179325
An online adaptive cooperation scheme for spectrum sensing based on a second-order statistical method
(IEEE-Inst Electrical Electronics Engineers Inc, 2012) Yarkan, Serhan; Töreyin, Behçet Uğur; Qaraqe, Khalid A.; Çetin, A. Enis; 19325
Spectrum sensing is one of the most important features of cognitive radio (CR) systems. Although spectrum sensing can be performed by a single CR, it is shown in the literature that cooperative techniques, including multiple CRs/sensors, improve the performance and reliability of spectrum sensing. Existing cooperation techniques usually assume a static communication scenario between the unknown source and sensors along with a fixed propagation environment class. In this paper, an online adaptive cooperation scheme is proposed for spectrum sensing to maintain the level of sensing reliability and performance under changing channel and environmental conditions. Each cooperating sensor analyzes second-order statistics of the received signal, which undergoes both correlated fast and slow fading. Autocorrelation estimation data from sensors are fused together by an adaptive weighted linear combination at the fusion center. Weight update operation is performed online through the use of orthogonal projection onto convex sets. Numerical results show that the performance of the proposed scheme is maintained for dynamically changing characteristics of the channel between an unknown source and sensors, even under different physical propagation environments. In addition, it is shown that the proposed cooperative scheme, which is based on second-order detectors, yields better results compared with the same fusion mechanism that is based on conventional energy detectors.
Citation Count: Günay, O...et al. (2012). Entropy-Functional-Based Online Adaptive Decision Fusion Framework With Application to Wildfire Detection in Video. IEEE Transactions On Image Processing, 21(5), 2853-2865. http://dx.doi.org/10.1109/TIP.2012.2183141
Entropy-Functional-Based Online Adaptive Decision Fusion Framework With Application to Wildfire Detection in Video
(IEEE-Inst Electrical Electronics Engineers Inc, 2012) Günay, Osman; Töreyin, Behçet Uğur; Köse, Kıvanç; Çetin, Enis; 19325
In this paper, an entropy-functional-based online adaptive decision fusion (EADF) framework is developed for image analysis and computer vision applications. In this framework, it is assumed that the compound algorithm consists of several subalgorithms, each of which yields its own decision as a real number centered around zero, representing the confidence level of that particular subalgorithm. Decision values are linearly combined with weights that are updated online according to an active fusion method based on performing entropic projections onto convex sets describing subalgorithms. It is assumed that there is an oracle, who is usually a human operator, providing feedback to the decision fusion method. A video-based wildfire detection system was developed to evaluate the performance of the decision fusion algorithm. In this case, image data arrive sequentially, and the oracle is the security guard of the forest lookout tower, verifying the decision of the combined algorithm. The simulation results are presented.
Citation Count: Yazar, A...et al. (2013). Fall detection using single-tree complex wavelet transform. Pattern Recognition Letters, 34(15), 1945-1952. http://dx.doi.org/10.1016/j.patrec.2012.12.010
Fall detection using single-tree complex wavelet transform
(Elsevier Science Bv, 2013) Yazar, Ahmet; Keskin, Furkan; Töreyin, Behçet Uğur; Çetin, A. Enis; 19325; 2147
The goal of Ambient Assisted Living (AAL) research is to improve the quality of life of the elderly and handicapped people and help them maintain an independent lifestyle with the use of sensors, signal processing and telecommunications infrastructure. Unusual human activity detection such as fall detection has important applications. In this paper, a fall detection algorithm for a low cost AAL system using vibration and passive infrared (PIR) sensors is proposed. The single-tree complex wavelet transform (ST-CWT) is used for feature extraction from vibration sensor signal. The proposed feature extraction scheme is compared to discrete Fourier transform and mel-frequency cepstrum coefficients based feature extraction methods. Vibration signal features are classified into "fall" and "ordinary activity" classes using Euclidean distance, Mahalanobis distance, and support vector machine (SVM) classifiers, and they are compared to each other. The PIR sensor is used for the detection of a moving person in a region of interest. The proposed system works in real-time on a standard personal computer.
Citation Count: Yazar, Ahmet; Çetin, A. Enis; Töreyin, B. Uǧur (2012). "Human activity classification using vibration and PIR sensors", 2012 20th Signal Processing and Communications Applications Conference, SIU 2012.
Human activity classification using vibration and PIR sensors
(2012) Yazar, Ahmet; Çetin, A. Enis; Töreyin, B. Uǧur; 19325
Fall detection is an important problem for elderly people living independently and people in need of care. In this paper, a fall detection method using seismic and passive infrared (PIR) sensors is proposed. Fast Fourier transform, mel-frequency cepstrum coefficients, and discrete wavelet transform based features are extracted for classification. Seismic signals are classified into "fall" and "not a fall" classes using support vector machines. Once a moving person is detected by the PIR sensor within a region of interest, fall is detected by fusing seismic and PIR sensor decisions. The proposed system is implemented on a standard personal computer and works in real-time. © 2012 IEEE.
Citation Count: Günay, Osman; Töreyin, Behçer Uğur; Çetin, Ahmet Enis (2011). "Online adaptive decision fusion framework based on projections onto convex sets with application to wildfire detection in video", Optical Engineering, Vol. 50, No. 2.
Online adaptive decision fusion framework based on projections onto convex sets with application to wildfire detection in video
(2011) Günay, Osman; Töreyin, Behçer Uğur; Çetin, Ahmet Enis; 19325
t. In this paper, an online adaptive decision fusion framework is developed for image analysis and computer vision applications. In this framework, it is assumed that the compound algorithm consists of several sub-algorithms, each of which yields its own decision as a real number centered around zero, representing the confidence level of that particular sub-algorithm. Decision values are linearly combined with weights that are updated online according to an active fusion method based on performing orthogonal projections onto convex sets describing sub-algorithms. It is assumed that there is an oracle, who is usually a human operator, providing feedback to the decision fusion method. A video-based wildfire detection system is developed to evaluate the performance of the algorithm in handling the problems where data arrives sequentially. In this case, the oracle is the security guard of the forest lookout tower verifying the decision of the combined algorithm. Simulation results are presented.
Citation Count: Çetin, A.E...et al. (2013). Video fire detection - Review. Digital Signal Processing, 23(6), 1827-1843. http://dx.doi.org/10.1016/j.dsp.2013.07.003
Video fire detection - Review
(Academic Press Inc Elsevier Science, 2013) Çetin, A. Enis; Dimitropoulos, Kosmas; Gouverneur, Benedict; Grammalidis, Nikos; Günay, Osman; Habiboğlu, Y. Hakan; Töreyin, Behçet Uğur; Verstockt, Steven; 19325; 2147
This is a review article describing the recent developments in Video based Fire Detection (VFD). Video surveillance cameras and computer vision methods are widely used in many security applications. It is also possible to use security cameras and special purpose infrared surveillance cameras for fire detection. This requires intelligent video processing techniques for detection and analysis of uncontrolled fire behavior. VFD may help reduce the detection time compared to the currently available sensors in both indoors and outdoors because cameras can monitor "volumes" and do not have transport delay that the traditional "point" sensors suffer from. It is possible to cover an area of 100 km(2) using a single pan-tilt-zoom camera placed on a hilltop for wildfire detection. Another benefit of the VFD systems is that they can provide crucial information about the size and growth of the fire, direction of smoke propagation
Citation Count: Erden, F...et al. (2012). Wavelet based flickering flame detector using differential PIR sensors. Fire Safety Journal, 53, 13-18. http://dx.doi.org/10.1016/j.firesaf.2012.06.006
Wavelet based flickering flame detector using differential PIR sensors
(Elsevier Science LTD, 2012) Erden, Fatih; Töreyin, Behçet Uğur; Soyer, E.Birey; İnaç, İhsan; Günay, Osman; Köse, Kıvanç; Çetin, A. Enis; 243050; 19325; 2147
A Pyro-electric Infrared (FIR) sensor based flame detection system is proposed using a Markovian decision algorithm. A differential PIR sensor is only sensitive to sudden temperature variations within its viewing range and it produces a time-varying signal. The wavelet transform of the FIR sensor signal is used for feature extraction from sensor signal and wavelet parameters are fed to a set of Markov models corresponding to the flame flicker process of an uncontrolled fire, ordinary activity of human beings and other objects. The final decision is reached based on the model yielding the highest probability among others. Comparative results show that the system can be used for fire detection in large rooms

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