Browsing by Subject "Wavelet analysis"

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Open Access
Çokyollu kanal parametre kestirimi için yeni bir dizilim sinyal işleme tekniği
(IEEE, 2007-06) Güldoǧan, Mehmet Burak; Arıkan, Orhan
Bu bildiride, çarpraz belirsizlik işlevinin kullanıldığı yeni bir dizilim sinyal işleme tekniği önerilmektedir. Geliştirilen teknik bir algılayıcı dizilimine gelen sinyallerden herbirinin geliş yönünü (GY), zaman gecikmesini Doppler kaymasını ve genliğini dürümlü bir sekilde kestirir. Önerilen Çarpraz Belirsizlik İşlevi - Yön Bulma (ÇBI-YB) tekniği ile Çoklu Sinyal Sınıflandırması (MUSIC) algoritmasının performansları sentetik sinyaller kullanılarak kök Ortalama Karesel Hata (kOKH) cinsinden değişik işaret Gürültü Oranı (İGO) değerleri için karşılaştırılmıştır. Önerilen tekniğin başarımı kayıt edilmiş çokyollu yüksek-enlem iyonosfer verileri üzerinde irdelenmiştir. Elde edilen sonuçlar, düşük İGO değerlerinde dahi çokyollu sinyal kaynaklarını ayırmada önerilen ÇBİ-YB tekniğinin ciddi başarım artışı sağladığını göstermektedir.
Open Access
Çokyollu ortamda çapraz belirsizlik işlevi-yön bulma tekniğinin başarım analizi
(IEEE, 2008-04) Güldoǧan, Mehmet Burak; Arıkan, Orhan
Bu bildiride, Çapraz Belirsizlik İşlevi-Yön Bulma (CAFDF) tekniğinin çokyollu ortamlardaki sinyallerin zaman gecikmesi, Doppler kayması, geliş yönü(GY) ve genlik kestirimindeki başarımı ile yiiksek çözünürlüklü algoritmalar olan Uzay-Almaşan Genelleşmiş Beklenti-Enbüyüitme (SAGE) ve Çoklu Sinyal Sınıflandırılması(MUSIC)'in sentetik sinyaller iizerindeki başarımları kıyaslanmıştır. Algoritmalann performansları, kök Ortalama Karesel Hata (kOKH) cinsinden degişik işaret Gürültü Oranı (iGO) değerlerinde Monte Carlo denemelerine dayalı olarak sunulmuştur. Sentetik kanallarda istatiksel kıyaslama amaçlı Cramer-Rao alt sınırları eklenmiştir. Simülasyon sonuçları göstermektedir ki, orta ve düşük iGO değerlerinde CAF-DF diğer iki algoritmaya göre üstünlük sağlamaktadır.
Open Access
Contact-free measurement of respiratory rate using infrared and vibration sensors
(Elsevier BV, 2015) Erden, F.; Alkar, A. Z.; Çetin, A. Enis
Respiratory rate is an essential parameter in many practical applications such as apnea detection, patient monitoring, and elderly people monitoring. In this paper, we describe a novel method and a contact-free multi-modal system which is capable of detecting human breathing activity. The multimodal system, which uses both differential pyro-electric infrared (PIR) and vibration sensors, can also estimate the respiratory rate. Vibration sensors pick up small vibrations due to the breathing activity. Similarly, PIR sensors pick up the thoracic movements. Sensor signals are sampled using a microprocessor board and analyzed on a laptop computer. Sensor signals are processed using wavelet analysis and empirical mode decomposition (EMD). Since breathing is almost periodic, a new multi-modal average magnitude difference function (AMDF) is used to detect the periodicity and the period in the processed signals. By fusing the data of two different types of sensors we achieve a more robust and reliable contact-free human breathing activity detection system compared to systems using only one specific type of sensors.
Open Access
Diferansiyel PIR algılayıcılarla dalgacık tabanlı alev tespiti
(IEEE, 2012-04) Erden, F.; Töreyin, B. U.; Soyer, E. B.; İnaç, İ.; Günay, O.; Köse, K.; Çetin, A. Enis
Bu makalede, diferansiyel kızılberisi algılayıcı (PIR) kullanılarak geliştirilen bir alev tespit sistemi önerilmektedir. Diferansiyel kızılberisi algılayıcılar, yalnızca görüş alanlarındaki ani sıcaklık değişikliklerine duyarlıdır ve zamanla değişen sinyaller üretir. Algılayıcı sinyaline ait dalgacık dönüşümü, öznitelik çıkarmak için kullanılır ve bu öznitelik vektörü hızlı titreşen kontrolsüz bir ateşin alevi ve bir kişinin yürümesi olaylarıyla eğitilmiş Markov modellerine sokulur. En yüksek olasılıkla sonuçlanan modele karar verilir. Karşılaştırmalı sonuçlar, sistemin geniş odalarda ateş tespiti için kullanılabileceğini düşündürmektedir.
Open Access
Flame detection system based on wavelet analysis of PIR sensor signals with an HMM decision mechanism
(IEEE, 2008-08) Ug̃ur Töreyin, B.; Soyer, E. Birey; Urfaliog̃lu, Onay; Çetin, A. Enis
In this paper, a flame detection system based on a pyroelectric (or passive) infrared (PIR) sensor is described. The flame detection system can be used for fire detection in large rooms. The flame flicker process of an uncontrolled fire and ordinary activity of human beings and other objects are modeled using a set of Hidden Markov Models (HMM), which are trained using the wavelet transform of the PIR sensor signal. Whenever there is an activity within the viewing range of the PIR sensor system, the sensor signal is analyzed in the wavelet domain and the wavelet signals are fed to a set of HMMs. A fire or no fire decision is made according to the HMM producing the highest probability. copyright by EURASIP.
Open Access
Progressive compression of digital elevation data using meshes
(IEEE, 2009-07) Köse, Kıvanç; Yılmaz, E.; Çetin, A. Enis
In this paper a new Digital Elevation Map (DEM) image compression algorithm is proposed. DEM image can be threated as a grayscale image, whose pixel values are the elevation values of the map points. The grayscale DEM image is compressed using an adaptive wavelet based image compression algorithm. The method, which is an extension of the progressive mesh compression takes advantage of the multiresolution property of the wavelets while coding the map images. This makes it possible to decode different resolutions of the map from the encoded bit stream providing a multiresolution display of a given map. Experimental results are presented. ©2009 IEEE.
Open Access
Projection-based wavelet denoising [lecture notes]
(Institute of Electrical and Electronics Engineers Inc., 2015) Çetin, A. Enis; Tofighi M.
In this lecture note, we describe a wavelet domain denoising method consisting of making orthogonal projections of wavelet (subbands) signals of the noisy signal onto an upside down pyramid-shaped region in a multidimensional space. Each horizontal slice of the upside down pyramid is a diamond shaped region and it is called an -ball. The upside down pyramid is called the epigraph set of the -norm cost function. We show that the method leads to soft-thresholding as in standard wavelet denoising methods. Orthogonal projection operations automatically determine the soft-threshold values of the wavelet signals. © 2015 IEEE.
Open Access
Unsupervised detection and localization of structural textures using projection profiles
(Elsevier BV, 2010) Yalniz, I. Z.; Aksoy, S.
The main goal of existing approaches for structural texture analysis has been the identification of repeating texture primitives and their placement patterns in images containing a single type of texture. We describe a novel unsupervised method for simultaneous detection and localization of multiple structural texture areas along with estimates of their orientations and scales in real images. First, multi-scale isotropic filters are used to enhance the potential texton locations. Then, regularity of the textons is quantified in terms of the periodicity of projection profiles of filter responses within sliding windows at multiple orientations. Next, a regularity index is computed for each pixel as the maximum regularity score together with its orientation and scale. Finally, thresholding of this regularity index produces accurate localization of structural textures in images containing different kinds of textures as well as non-textured areas. Experiments using three different data sets show the effectiveness of the proposed method in complex scenes. © 2010 Elsevier Ltd. All rights reserved.
Open Access
Volatile organic compound plume detection using wavelet analysis of video
(IEEE, 2008-10) Töreyin, B. Uğur; Çetin, A. Enis
A video based method to detect volatile organic compounds (VOC) leaking out of process equipments used in petrochemical refineries is developed. Leaking VOC plume from a damaged component causes edges present in image frames loose their sharpness. This leads to a decrease in the high frequency content of the image. The background of the scene is estimated and decrease of high frequency energy of the scene is monitored using the spatial wavelet transforms of the current and the background images. Plume regions in image frames are analyzed in low-band sub-images, as well. Image frames are compared with their corresponding low-band images. A maximum likelihood estimator (MLE) for adaptive threshold estimation is also developed in this paper. © 2008 IEEE.
Open Access
Wavelet based real-time smoke detection in video
(IEEE, 2005-09) Töreyin, B. Uğur; Dedeoǧlu, Yiğithan; Çetin, A. Enis
A method for smoke detection in video is proposed. It is assumed the camera monitoring the scene is stationary. Since the smoke is semi-transparent, edges of image frames start loosing their sharpness and this leads to a decrease in the high frequency content of the image. To determine the smoke in the field of view of the camera, the background of the scene is estimated and decrease of high frequency energy of the scene is monitored using the spatial wavelet transforms of the current and the background images. Edges of the scene are especially important because they produce local extrema in the wavelet domain. A decrease in values of local extrema is also an indicator of smoke. In addition, scene becomes grayish when there is smoke and this leads to a decrease in chrominance values of pixels. Periodic behavior in smoke boundaries and convexity of smoke regions are also analyzed. All of these clues are combined to reach a final decision.