Benveniste, R. | Ünsalan, Cem

Conference Object | 2010 | Lecture Notes in Electrical Engineering62 LNEE , pp.241 - 244

Three dimensional range data provides useful information for computer vision, computer graphics, and object recognition applications. For these, extracting the range data reliably is utmost important. Therefore, various range scanners based on different operating principles are proposed in the literature. Although these scanners can be used in diverse applications, most of them cannot be used to scan shiny objects under ambient light. This is a severe restriction. We propose color invariant based binary and ternary coded structured light range scanners to solve this problem. We hypothesize that, by using color invariants we can elim . . .inate the effects of highlights and ambient light in the scanning process. Therefore, we can extract the range data of shiny and matte objects in a robust manner. We implemented three different range scanners to test our hypothesis. We performed tests on various objects and provided their range data. © 2011 Springer Science+Business Media B.V Daha fazlası Daha az

Irgan, K. | Ünsalan, Cem | Baydere, Ş.

Conference Object | 2010 | Lecture Notes in Electrical Engineering62 LNEE , pp.191 - 194

25th International Symposium on Computer and Information Sciences, ISCIS 2010 -- 22 September 2010 through 24 September 2010 -- London -- 82255

Altintaş, A. | Ünsalan, Cem | Keskin, A.U. | Yencilek, F.

Conference Object | 2010 | 2010 15th National Biomedical Engineering Meeting, BIYOMUT2010 , pp.191 - 194

Extracorporeal Shock Wave Lithotrispy (ESWL) is a procedure based on sound waves to crash kidney stones on the focus. The sound waves are sent to the body of patient when the kidney stone is not even on the focus. When the stone is not on the focus, the sound waves can damage the soft tissue of the kidney. This damage can be prevented by a feedback mechanism that determines the place of kidney stones depending on the images taken from ESWL device. In this study, an automated system is developed to detect kidney stones from X ray images. ©2010 IEEE.

Sertel, O. | Ünsalan, Cem

Conference Object | 2006 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)4105 LNCS , pp.745 - 752

In this study, we focus on model reconstruction for 3D objects using range images. We propose a crude range image alignment method to overcome the initial estimation problem of the iterative closest point (ICP) algorithm using edge points of range images. Different from previous edge detection methods, we first obtain a function representation of the range image in spherical coordinates. This representation allows detecting smooth edges on the object surface easily by a zero crossing edge detector. We use ICP on these edges to align patches in a crude manner. Then, we apply ICP to the whole point set and obtain the final alignment. . . .This dual operation is performed extremely fast compared to directly aligning the point sets. We also obtain the edges of the 3D object model while registering it. These edge points may be of use in 3D object recognition and classification. © Springer-Verlag Berlin Heidelberg 2006 Daha fazlası Daha az

Ilsever, M. | Ünsalan, Cem

Conference Object | 2013 | RAST 2013 - Proceedings of 6th International Conference on Recent Advances in Space Technologies , pp.115 - 119

One of the most important applications of remote sensing is detecting and analyzing man-made structures in aerial and satellite images. Buildings deserve specific consideration among man-made structures. Manual detection is the one way of labeling the buildings. Recent satellite image resolutions allow researchers manual detection. However, this approach is cumbersome and prone to errors. Therefore, an automated method is needed. Unfortunately, the solution is not straightforward due to various factors. In this study, we propose an adaptation of an earlier successful method, Histogram of Oriented Gradients, to building detection. We . . . test our method on several Ikonos satellite images and provide the results. © 2013 IEEE Daha fazlası Daha az

Özcan, A.H. | Ünsalan, Cem

Conference Object | 2016 | 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings , pp.429 - 432

Automated object detection in remotely sensed data has gained wide application areas due to increased sensor resolution. In this study, we propose a novel building detection method using high resolution DSM data and true orthophoto image. In the proposed method, DSM feature points and NDVI are obtained. Then, they are used for spatial voting to generate a building probability map. Local maxima of this map are used as seed points for segmentation. For this purpose, a morphology based segmentation method is proposed. This way, buildings are detected from DSM data. We tested our method on ISPRS semantic labeling dataset and obtained pr . . .omising results. © 2016 IEEE Daha fazlası Daha az

Benveniste, R. | Ünsalan, Cem

Conference Object | 2010 | SIU 2010 - IEEE 18th Signal Processing and Communications Applications Conference , pp.292 - 295

To extract the range data of objects, there are various range scanners based on different principles. Among these, structured light based range scanners are mostly used. In these systems, coded light stripes are projected onto the object. Using the bending of these light stripes on the object and the triangulation principle, range information can be obtained. This method is used in most industrial range scanners, since it is simple and fast. The major problem with these range scanners is in scanning shiny objects. They can not be used to scan shiny objects reliably. The main reason for this problem is that the extra light projected . . .onto the object from the environment. This light is projected back from the object and disturbs the original projected binary coded light structure. Therefore, range data of the shiny objects can not be obtained reliably using these scanners. In this study, we developed a color based binary structured light system to solve this problem. To eliminate the effect of the ambient light, we used a color invariant. This way, we were able to extract the range data of shiny objects in a robust manner. We provided the range data of various test objects obtained with our range scanner. ©2010 IEEE Daha fazlası Daha az

Özcan, A.H. | Sayar, Y. | Hisar, D. | Ünsalan, Cem

Conference Object | 2016 | 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings , pp.453 - 456

As satellite images cover wide areas and obtaining them has become easier, using these images in agriculture has become an important research area. Especially, satellite images can be used in seasonal crop estimation. Obtaining the number of trees in a region, with the size of each tree, gives the approximate amount of crop that can be harvested from that region. In this study, we propose a voting based method on grayscale satellite images. To test the proposed method, we picked eight satellite images containing 2668 trees. We summarized the obtained results in this study. © 2016 IEEE.

Benveniste, R. | Ünsalan, Cem

Conference Object | 2010 | Proceedings - International Conference on Pattern Recognition , pp.798 - 801

Object range data provide valuable information in recognition and modeling applications. Therefore, it is extremely important to reliably extract the range data from a given object. There are various range scanners based on different principles. Among these, structured light based range scanners deserve spacial attention. In these systems, coded light stripes are projected onto the object. Using the bending of these light stripes on the object and the triangulation principle, range information can be obtained. Since this method is simple and fast, it is used in most industrial range scanners. Unfortunately, these range scanners can . . .not scan shiny objects reliably. The main reason is either highlights on the shiny object or the ambient light in the environment. These disturb the coding by illumination. As the code is changed, the range data extracted from it will also be disturbed. In this study, we propose a color invariant based binary coded structured light range scanner to solve this problem. The color invariant used can eliminate the effects of highlights on the object and the ambient light from the environment. This way, we can extract the range data of shiny objects in a robust manner. To test our method, we developed a prototype range scanner. We provide the obtained range data of various test objects with our range scanner. © 2010 IEEE Daha fazlası Daha az

Ünsalan, Cem | Boyer, K.L.

Conference Object | 2004 | Proceedings - International Conference on Pattern Recognition3 , pp.49 - 52

Maps are vital tools for most government agencies and consumers. However, their manual generation and updating is tedious and time consuming. As a step toward automatic map generation, we introduce a novel system to detect houses and street networks in IKONOS multispectral images. Our system consists of four main blocks: multispectral analysis to detect cultural activity, segmentation of possible human activity regions, decomposition of segmented images, and graph theoretical algorithms to extract the street network and to detect houses over the decompositions. We tested our system on a large and diverse data set. Our results indica . . .te the usefulness of our system in detecting houses and street networks, hence generating automated maps Daha fazlası Daha az

Sirmacek, B. | Ünsalan, Cem

Conference Object | 2011 | IEEE Transactions on Geoscience and Remote Sensing49 ( 1 PART 1 ) , pp.211 - 221

Detecting buildings from very high resolution (VHR) aerial and satellite images is extremely useful in map making, urban planning, and land use analysis. Although it is possible to manually locate buildings from these VHR images, this operation may not be robust and fast. Therefore, automated systems to detect buildings from VHR aerial and satellite images are needed. Unfortunately, such systems must cope with major problems. First, buildings have diverse characteristics, and their appearance (illumination, viewing angle, etc.) is uncontrolled in these images. Second, buildings in urban areas are generally dense and complex. It is h . . .ard to detect separate buildings from them. To overcome these difficulties, we propose a novel building detection method using local feature vectors and a probabilistic framework. We first introduce four different local feature vector extraction methods. Extracted local feature vectors serve as observations of the probability density function (pdf) to be estimated. Using a variable-kernel density estimation method, we estimate the corresponding pdf. In other words, we represent building locations (to be detected) in the image as joint random variables and estimate their pdf. Using the modes of the estimated density, as well as other probabilistic properties, we detect building locations in the image. We also introduce data and decision fusion methods based on our probabilistic framework to detect building locations. We pick certain crops of VHR panchromatic aerial and Ikonos satellite images to test our method. We assume that these crops are detected using our previous urban region detection method. Our test images are acquired by two different sensors, and they have different spatial resolutions. Also, buildings in these images have diverse characteristics. Therefore, we can test our methods on a diverse data set. Extensive tests indicate that our method can be used to automatically detect buildings in a robust and fast manner in Ikonos satellite and our aerial images. © 2006 IEEE Daha fazlası Daha az

Yagmur Gök, M. | Sagiroglu, M.Ş. | Ünsalan, Cem | Gören, S.

Conference Object | 2013 | 2013 21st Signal Processing and Communications Applications Conference, SIU 2013 , pp.211 - 221

Smith Waterman Algorithm is a widely used tool in bioinformatics to align reads from aligning to a reference in whole genome sequencing. Mapping millions of sequences read from sequencing is a computationally expensive operation. Accuracy and performance are two important aspects of this process. FPGA based solutions are widely studied. In this paper we tried to achieve a better mapping accuracy for optimum alignment using quality scores of the bases of read sequences while keeping the performance high. We are offering a new Smith Waterman processing unit and systolic array based on quality scores. © 2013 IEEE.