Browsing by Subject "Pattern matching"

Now showing 1 - 12 of 12

Open Access
Çizge kesit yöntemi ile hiperspektral görüntülerde anomali tabanlı hedef tespiti
(IEEE, 2015-05) Batı, E.; Erdinç, Acar; Çeşmeci, D.; Çalışkan, A.; Koz, A.; Aksoy, Selim; Ertürk, S.; Alatan, A. A.
Hiperspektral hedef tespiti için yürütülen çalışmalar genel olarak iki sınıfta degerlendirilebilir. İlk sınıf olan anomali tespit yöntemlerinde, hedefin görüntünün geri kalanından farklı oldugu bilgisi kullanılarak görüntü analiz edilmektedir. Diğer sınıfta ise daha önceden bilgisi edinilmiş hedefe ait spektral imza ile görüntüdeki herbir piksel arasındaki benzerlik bulunarak hedefin konumu tespit edimektedir. Her iki sınıf yöntemin de önemli bir dezavantajı hiperspektral görüntü piksellerini bagımsız olarak degerlendirip, aralarındaki komşuluk ilişkilerini gözardı etmesidir. Bu makalede anomali tespit ve imza tabanlı tespit yakla¸sımlarını, pikseller arası komşuluk ilişkilerini de göz önünde bulundurarak birleştiren çizge yaklaşımına dayalı yeni bir yöntem önerilmiştir. Hedeflerin hem imza bilgisine sahip olundugu hem de anomali sayılabilecek ölçülerde olduğu varsayılarak önerilen çizge yaklaşımında önplan için imza bilgisi kullanan özgün bir türev tabanlı uyumlu filtre önerilmiştir. Arkaplan için ise seyreklik bilgisi kullanarak Gauss karışım bileşeni kestirimi yapan yeni bir anomali tespit yöntemi geliştirilmiştir. Son olarak komşular arası benzerligi tanımlamak için ise spektral bir benzerlik ölçütü olan spektral açı eleştiricisi kullanılmıştır. Önerilen çizge tabanlı yöntemin önplan, arkaplan ve komşuluk ilişkilerini uygun şekilde birleştirdigi ve önceki yöntemlere göre hedefi gürültüden arınmış bir bütün şeklinde başarıyla tespit edebildigi gözlemlenmiştir. The studies on hyperspectral target detection until now, has been treated in two approaches. Anomaly detection can be considered as the first approach, which analyses the hyperspectral image with respect to the difference between target and the rest of the hyperspectral image. The second approach compares the previously obtained spectral signature of the target with the pixels of the hyperspectral image in order to localize the target. A distinctive disadvantage of the aforementioned approaches is to treat each pixel of the hyperspectral image individually, without considering the neighbourhood relations between the pixels. In this paper, we propose a target detection algorithm which combines the anomaly detection and signature based hyperspectral target detection approaches in a graph based framework by utilizing the neighbourhood relations between the pixels. Assuming that the target signature is available and the target sizes are in the range of anomaly sizes, a novel derivative based matched filter is first proposed to model the foreground. Second, a new anomaly detection method which models the background as a Gaussian mixture is developed. The developed model estimates the optimal number of components forming the Gaussian mixture by means of utilizing sparsity information. Finally, the similarity of the neighbouring hyperspectral pixels is measured with the spectral angle mapper. The overall proposed graph based method has successfully combined the foreground, background and neighbouring information and improved the detection performance by locating the target as a whole object free from noises. © 2015 IEEE.
Open Access
Comparison and combination of two novel commercial detection methods
(IEEE, 2004-06) Duygulu, Pınar; Chen, M.-Y.; Hauptmann, A.
Detection and removal of commercials plays an important role when searching for important broadcast news video material. In this study, two novel approaches are proposed based on two distinctive characteristics of commercials, namely, repetitive use of commercials over time and distinctive color and audio features. Furthermore, proposed strategies for combining the results of the two methods yield even better performance. Experiments show over 90% recall and precision on a test set of 5 hours of ABC and CNN broadcast news data.
Open Access
Cross-term free based bistatic radar system using sparse least squares
(SPIE, 2015) Sevimli, R. Akın; Çetin, A. Enis
Passive Bistatic Radar (PBR) systems use illuminators of opportunity, such as FM, TV, and DAB broadcasts. The most common illuminator of opportunity used in PBR systems is the FM radio stations. Single FM channel based PBR systems do not have high range resolution and may turn out to be noisy. In order to enhance the range resolution of the PBR systems algorithms using several FM channels at the same time are proposed. In standard methods, consecutive FM channels are translated to baseband as is and fed to the matched filter to compute the range-Doppler map. Multichannel FM based PBR systems have better range resolution than single channel systems. However superious sidelobe peaks occur as a side effect. In this article, we linearly predict the surveillance signal using the modulated and delayed reference signal components. We vary the modulation frequency and the delay to cover the entire range-Doppler plane. Whenever there is a target at a specific range value and Doppler value the prediction error is minimized. The cost function of the linear prediction equation has three components. The first term is the real-part of the ordinary least squares term, the second-Term is the imaginary part of the least squares and the third component is the l2-norm of the prediction coefficients. Separate minimization of real and imaginary parts reduces the side lobes and decrease the noise level of the range-Doppler map. The third term enforces the sparse solution on the least squares problem. We experimentally observed that this approach is better than both the standard least squares and other sparse least squares approaches in terms of side lobes. Extensive simulation examples will be presented in the final form of the paper.
Open Access
Energy consumption forecasting via order preserving pattern matching
(IEEE, 2014-12) Vanlı, N. Denizcan; Sayın, Muhammed O.; Yıldız, Hikmet; Göze, Tolga; Kozat, Süleyman S.
We study sequential prediction of energy consumption of actual users under a generic loss/utility function. Particularly, we try to determine whether the energy usage of the consumer will increase or decrease in the future, which can be subsequently used to optimize energy consumption. To this end, we use the energy consumption history of the users and define finite state (FS) predictors according to the relative ordering patterns of these past observations. In order to alleviate the overfitting problems, we generate equivalence classes by tying several states in a nested manner. Using the resulting equivalence classes, we obtain a doubly exponential number of different FS predictors, one among which achieves the smallest accumulated loss, hence is optimal for the prediction task. We then introduce an algorithm to achieve the performance of this FS predictor among all doubly exponential number of FS predictors with a significantly reduced computational complexity. Our approach is generic in the sense that different tying configurations and loss functions can be incorporated into our framework in a straightforward manner. We illustrate the merits of the proposed algorithm using the real life energy usage data. © 2014 IEEE.
Open Access
Osmanlı arşivleri içerik-bazlı sorgulama (İBS) sistemi
(2006-04) Altıngövde, İsmail Şengör; Şaykol, Ediz; Ulusoy, Özgür; Güdükbay, Uğur; Çetin, A. Enis; Göçmen, M.
We propose a content-based retrieval (CBR) system for digital Ottoman archive documents. In this system, the symbols extracted from the documents are matched with the most similar one in the symbol library, which is created in a supervised manner. The users specify queries by marking a region on an example document and the system retrieves all documents that include the symbols found in the query region. A prototype of the system is currently available on the Web. © 2006 IEEE.
Open Access
Pasif bistatik radarlarda seyreklik temellli ters evrişim kullanılarak hedef tespiti
(IEEE, 2015-05) Arslan, Musa Tunç; Tofighi, Mohammad; Çetin, A. Enis
Bu bildiride pasif radar (PR) sistemlerinin menzil çözünürlüğünü artırmak için seyreklik tabanlı bir ters evrişim yöntemi sunulmaktadır. PR sistemlerinin iki boyutlu uyumlu süzgeç çıktısı bir ters evrişim problemli gibi düşünülerek incelenmektedir. Ters evrişim algoritması, hedeflerin zaman kaymaları ve l1 norm benzeri dışbükey maliyet fonksiyonlarının epigraf kümelerini temsil eden hiperdüzlemler üzerine izdüşümü temellidir. Bütün kısıt kümeleri kapalı ve dışbükey olduklarından dolayı yinelemeli algoritma yakınsamaktadır. FM tabanlı PR sistemleri üzerinde benzetim sonuçları sunulmuştur. Algoritma frekans uzayı tabanlı ters evrişim yöntemlerine göre daha yüksek performansa sahiptir.
Open Access
Range resolution improvement in passive bistatic radars using nested FM channels and least squares approach
(SPIE, 2015) Arslan, Musa Tunç; Tofighi, Muhammad; Sevimli, Rasim Akın; Çetin, A. Enis
One of the main disadvantages of using commercial broadcasts in a Passive Bistatic Radar (PBR) system is the range resolution. Using multiple broadcast channels to improve the radar performance is offered as a solution to this problem. However, it suffers from detection performance due to the side-lobes that matched filter creates for using multiple channels. In this article, we introduce a deconvolution algorithm to suppress the side-lobes. The two-dimensional matched filter output of a PBR is further analyzed as a deconvolution problem. The deconvolution algorithm is based on making successive projections onto the hyperplanes representing the time delay of a target. Resulting iterative deconvolution algorithm is globally convergent because all constraint sets are closed and convex. Simulation results in an FM based PBR system are presented.
Open Access
Retrieval of Ottoman documents
(ACM, 2006-10) Ataer, Esra; Duygulu, Pınar
There is a growing need to access historical Ottoman documents stored in large archives and therefore managing tools for automatic searching, indexing and transcription of these documents is required. In this paper, we present a method for the retrieval of Ottoman documents based on word matching. The method first successfully segments the documents into word images and then uses a hierarchical matching technique to find the similar instances of the word images. The experiments show that even with simple features promising results can be achieved. Copyright 2006 ACM.
Open Access
Shortest unique substring query revisited
(Springer, Cham, 2014) Ileri, Atalay Mert; Külekci, M.O.; Xu, B.
We revisit the problem of finding shortest unique substring (SUS) proposed recently by Pei et al. (ICDE'13). We propose an optimal O(n) time and space algorithm that can find an SUS for every location of a string of size n and thus significantly improve their O(n 2) time complexity. Our method also supports finding all the SUSes covering every location, whereas theirs can find only one SUS for every location. Further, our solution is simpler and easier to implement and can also be more space efficient in practice, since we only use the inverse suffix array and the longest common prefix array of the string, while their algorithm uses the suffix tree of the string and other auxiliary data structures. Our theoretical results are validated by an empirical study that shows our method is much faster and more space-saving. © 2014 Springer International Publishing Switzerland.
Open Access
Subband domain coding of binary textual images for document archiving
(Institute of Electrical and Electronics Engineers, 1999-10) Gerek, Ö. N.; Çetin, A. Enis; Tewfik, A. H.; Atalay, V.
In this work, a subband domain textual image compression method is developed. The document image is first decomposed into subimages using binary subband decompositions. Next, the character locations in the subbands and the symbol library consisting of the character images are encoded. The method is suitable for keyword search in the compressed data. It is observed that very high compression ratios are obtained with this method. Simulation studies are presented.
Open Access
Turkish factoid question answering using answer pattern matching
(2009) Pala Er, Nagehan
Efficiently locating information on the Web has become one of the most important challenges in the last decade. The Web Search Engines have been used to locate the documents containing the required information. However, in many situations a user wants a particular piece of information rather than a document set. Question Answering (QA) systems have addressed this problem and they return explicit answers to questions rather than set of documents. Questions addressed by QA systems can be categorized into five categories: factoid, list, definition, complex, and speculative questions. A factoid question has exactly one correct answer, and the answer is mostly a named entity like person, date, or location. In this thesis, we develop a pattern matching approach for a Turkish Factoid QA system. In TREC-10 QA track, most of the question answering systems used sophisticated linguistic tools. However, the best performing system at the track used only an extensive list of surface patterns; therefore, we decided to investigate the potential of answer pattern matching approach for our Turkish Factoid QA system. We try different methods for answer pattern extraction such as stemming and named entity tagging. We also investigate query expansion by using answer patterns. Several experiments have been performed to evaluate the performance of the system. Compared with the results of the other factoid QA systems, our methods have achieved good results. The results of the experiments show that named entity tagging improves the performance of the system.
Open Access
A virtual garment design and simulation system
(IEEE, 2007-07) Durupınar, Funda; Güdükbay, Uğur
In this paper, a 3D graphics environment for virtual garment design and simulation is presented. The proposed system enables the three dimensional construction of a garment from its cloth panels, for which the underlying structure is a mass-spring model. The garment construction process is performed through automatic pattern generation, posterior correction, and seaming. Afterwards, it is possible to do fitting on virtual mannequins as if in a real life tailor's workshop. The system provides the users with the flexibility to design their own garment patterns and make changes on the garment even after the dressing of the model. Furthermore, rendering alternatives for the visualization of knitted and woven fabric are presented. © 2007 IEEE.