Browsing by Subject "Textures"
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Item Open Access BilVideo: Design and implementation of a video database management system(Springer, 2005) Dönderler, M. E.; Şaykol, E.; Arslan, U.; Ulusoy, Özgür; Güdükbay, UğurWith the advances in information technology, the amount of multimedia data captured, produced, and stored is increasing rapidly. As a consequence, multimedia content is widely used for many applications in today's world, and hence, a need for organizing this data, and accessing it from repositories with vast amount of information has been a driving stimulus both commercially and academically. In compliance with this inevitable trend, first image and especially later video database management systems have attracted a great deal of attention, since traditional database systems are designed to deal with alphanumeric information only, thereby not being suitable for multimedia data. In this paper, a prototype video database management system, which we call BilVideo, is introduced. The system architecture of BilVideo is original in that it provides full support for spatio-temporal queries that contain any combination of spatial, temporal, object-appearance, external-predicate, trajectory-projection, and similarity-based object-trajectory conditions by a rule-based system built on a knowledge-base, while utilizing an object-relational database to respond to semantic (keyword, event/activity, and category-based), color, shape, and texture queries. The parts of BilVideo (Fact-Extractor, Video-Annotator, its Web-based visual query interface, and its SQL-like textual query language) are presented, as well. Moreover, our query processing strategy is also briefly explained. © 2005 Springer Science + Business Media, Inc.Item Open Access HMM based method for dynamic texture detection(IEEE, 2007) Töreyin, Behçet Uğur; Çetin, A. EnisA method for detection of dynamic textures in video is proposed. It is observed that the motion vectors of most of the dynamic textures (e.g. sea waves, swaying tree leaves and branches in the wind, etc.) exhibit random motion. On the other hand, regular motion of ordinary video objects has well-defined directions. In this paper, motion vectors of moving objects are estimated and tracked based on a minimum distance based metric. The direction of the motion vectors are then quantized to define two threestate Markov models corresponding to dynamic textures and ordinary moving objects with consistent directions. Hidden Markov Models (HMMs) are used to classify the moving objects in the final step of the algorithm.Item Open Access MPEG-7 uyumlu video veri tabanlari için önemli nesnelerin otomatik olarak bulunmasi(IEEE, 2008-04) Baştan, Muhammed; Güdükbay, Uğur; Ulusoy, ÖzgürBu çalışma, genel olarak nesneye dayalı endekslemeyi destekleyen, özel olarak MPEG-7 uyumlu veritabanları için, videolardan önemli nesnelerin otomatik olarak çıkarılmasını saglayabilecek bir yöntem sunmaktadır. Şimdiye kadar yapılan benzer çalışmalar genellikle resimler üzerinde yoğunlaşmış ve sadece ilk bakışta dikkati çeken alanları bulmaya çalışmıştır. Önerilen yöntem ise videolar üzerinde çalışmak için tasarlanmış olup sadece ilk bakışta dikkat çeken bölgelerin değil, videonun endekslenmesi için önemli sayılabilecek bölgelerin de bulunabilmesini amaçlamaktadır. Bunun için önce video kareleri bölütlere ayrılmakta, sonra her bölüt için yerel ve genel renk, biçim, doku ve hareket bilgileri hesaplanmakta, son olarak bu özellikler kullanılarak eğitilmiş bir destek vektor makinesi (SVM) kullanılarak bölgelerin önemli olup olmadığına karar verilmektedir. İlk deney sonuçları önerilen y öntemin başarılı olduğunu ve elde edilen nesnelerin öncekilere g öre anlamsal olarak daha iyi olduğunu göstermektedir. We describe a method to automatically extract video objects, which are important for object-based indexing of videos in an MPEG-7 compliant video database system. Most of the existing salient object detection approaches detect visually conspicuous image structures, while our method aims to find regions that may be important for indexing in a video database system. Our method works on a shot basis. We first segment each frame to obtain homogeneous regions in terms of color and texture. Then, we extract a set of local and global color, shape, texture and motion features for each region. Finally, the regions are classified as being salient or non-salient using SVMs trained on a few hundreds of example regions. Experimental results from news video segments show that the proposed method is more effective in extracting the important regions in terms of human visual perception. ©2008 IEEE.Item Open Access Object-oriented texture analysis for the unsupervised segmentation of biopsy images for cancer detection(Elsevier BV, 2009-06) Tosun, A. B.; Kandemir, M.; Sokmensuer, C.; Gunduz Demir, C.Staining methods routinely used in pathology lead to similar color distributions in the biologically different regions of histopathological images. This causes problems in image segmentation for the quantitative analysis and detection of cancer. To overcome this problem, unlike previous methods that use pixel distributions, we propose a new homogeneity measure based on the distribution of the objects that we define to represent tissue components. Using this measure, we demonstrate a new object-oriented segmentation algorithm. Working with colon biopsy images, we show that this algorithm segments the cancerous and normal regions with 94.89 percent accuracy on the average and significantly improves the segmentation accuracy compared to its pixel-based counterpart. © 2008 Elsevier Ltd. All rights reserved.Item Open Access Segmentation-based extraction of important objects from video for object-based indexing(IEEE, 2008-06) Baştan, Muhammet; Güdükbay, Uğur; Ulusoy, ÖzgürWe describe a method to automatically extract important video objects for object-based indexing. Most of the existing salient object detection approaches detect visually conspicuous structures in images, while our method aims to find regions that may be important for indexing in a video database system. Our method works on a shot basis. We first segment each frame to obtain homogeneous regions in terms of color and texture. Then, we extract a set of regional and inter-regional color, shape, texture and motion features for all regions, which are classified as being important or not using SVMs trained on a few hundreds of example regions. Finally, each important region is tracked within each shot for trajectory generation and consistency check. Experimental results from news video sequences show that the proposed approach is effective. © 2008 IEEE.Item Open Access Texture mapping on geometrical models(Bilkent University, 1989) Açıkgöz, Oktay AydınThe contribution of the visual effects of textures is an important aspect in generating images of real objects. Texture mapping is a very successful technique in this respect. Texture mapping can be subdivided into two fundamental topics; the geometric mapping and the filtering. The texture mapping system developed in this study is adaptable to different types of geometric models. Superqueadric, Bezier or b-spline surfaces can be mapped with textures. The geometric modeling and the texture synthesis subsystems were also implemented for this purpose. The system works in an interactive manner, the user describes the geometric model and the texture and gets the result in a reasonable amount of time. The speed and the usability of the system by a naive user are the keypoints of implementation.Item Open Access Texturing of titanium (Ti6Al4V) medical implant surfaces with MHz-repetition-rate femtosecond and picosecond Yb-doped fiber lasers(Optical Society of American (OSA), 2011) Erdoǧan, M.; Öktem, B.; Kalaycioǧlu H.; Yavaş, S.; Mukhopadhyay P.K.; Eken, K.; Özgören, K.; Aykaç, Y.; Tazebay, U.H.; Ilday F.O.We propose and demonstrate the use of short pulsed fiber lasers in surface texturing using MHz-repetition-rate, microjoule- and sub-microjoule-energy pulses. Texturing of titanium-based (Ti6Al4V) dental implant surfaces is achieved using femtosecond, picosecond and (for comparison) nanosecond pulses with the aim of controlling attachment of human cells onto the surface. Femtosecond and picosecond pulses yield similar results in the creation of micron-scale textures with greatly reduced or no thermal heat effects, whereas nanosecond pulses result in strong thermal effects. Various surface textures are created with excellent uniformity and repeatability on a desired portion of the surface. The effects of the surface texturing on the attachment and proliferation of cells are characterized under cell culture conditions. Our data indicate that picosecond-pulsed laser modification can be utilized effectively in low-cost laser surface engineering of medical implants, where different areas on the surface can be made cell-attachment friendly or hostile through the use of different patterns. © 2011 Optical Society of America.Item Open Access Tissue object patterns for segmentation in histopathological images(ACM, 2011) Gündüz-Demir, ÇiğdemIn the current practice of medicine, histopathological examination is the gold standard for routine clinical diagnosis and grading of cancer. However, as this examination involves the visual analysis of biopsies, it is subject to a considerable amount of observer variability. In order to decrease the variability, it has been proposed to develop systems that mathematically model the histopathological tissue images and automate the analysis. Segmentation constitutes the first step for most of these automated systems. Nevertheless, the segmentation in histopathological images remains a challenging task since these images typically show variances due to their complex nature and may include a large amount of noise and artifacts due to the tissue preparation procedures. In our research group, we recently developed different segmentation algorithms that rely on representing a tissue image with a set of tissue objects and using the structural pattern of these objects in segmentation. In this paper, we review these segmentation algorithms, discussing their clinical demonstrations on colon tissues. © 2011 ACM.Item Open Access Unsupervised tissue image segmentation through object-oriented texture(IEEE, 2010) Tosun, Akif Burak; Sokmensuer, C.; Gündüz-Demir, ÇiğdemThis paper presents a new algorithm for the unsupervised segmentation of tissue images. It relies on using the spatial information of cytological tissue components. As opposed to the previous study, it does not only use this information in defining its homogeneity measures, but it also uses it in its region growing process. This algorithm has been implemented and tested. Its visual and quantitative results are compared with the previous study. The results show that the proposed segmentation algorithm is more robust in giving better accuracies with less number of segmented regions. © 2010 IEEE.Item Open Access Wavelet domain textual coding of Ottoman script images(SPIE, 1996-03) Gerek, Ömer. N.; Çetin, A. Enis; Tewfik, A. H.Image coding using wavelet transform, DCT, and similar transform techniques is well established. On the other hand, these coding methods neither take into account the special characteristics of the images in a database nor are they suitable for fast database search. In this paper, the digital archiving of Ottoman printings is considered. Ottoman documents are printed in Arabic letters. Witten et al. describes a scheme based on finding the characters in binary document images and encoding the positions of the repeated characters This method efficiently compresses document images and is suitable for database research, but it cannot be applied to Ottoman or Arabic documents as the concept of character is different in Ottoman or Arabic. Typically, one has to deal with compound structures consisting of a group of letters. Therefore, the matching criterion will be according to those compound structures. Furthermore, the text images are gray tone or color images for Ottoman scripts for the reasons that are described in the paper. In our method the compound structure matching is carried out in wavelet domain which reduces the search space and increases the compression ratio. In addition to the wavelet transformation which corresponds to the linear subband decomposition, we also used nonlinear subband decomposition. The filters in the nonlinear subband decomposition have the property of preserving edges in the low resolution subband image.