Browsing by Subject "Novel methods"

Now showing 1 - 8 of 8

Open Access
Automatic detection of geospatial objects using multiple hierarchical segmentations
(Institute of Electrical and Electronics Engineers, 2008-07) Akçay, H. G.; Aksoy, S.
The object-based analysis of remotely sensed imagery provides valuable spatial and structural information that is complementary to pixel-based spectral information in classification. In this paper, we present novel methods for automatic object detection in high-resolution images by combining spectral information with structural information exploited by using image segmentation. The proposed segmentation algorithm uses morphological operations applied to individual spectral bands using structuring elements in increasing sizes. These operations produce a set of connected components forming a hierarchy of segments for each band. A generic algorithm is designed to select meaningful segments that maximize a measure consisting of spectral homogeneity and neighborhood connectivity. Given the observation that different structures appear more clearly at different scales in different spectral bands, we describe a new algorithm for unsupervised grouping of candidate segments belonging to multiple hierarchical segmentations to find coherent sets of segments that correspond to actual objects. The segments are modeled by using their spectral and textural content, and the grouping problem is solved by using the probabilistic latent semantic analysis algorithm that builds object models by learning the object-conditional probability distributions. The automatic labeling of a segment is done by computing the similarity of its feature distribution to the distribution of the learned object models using the Kullback-Leibler divergence. The performances of the unsupervised segmentation and object detection algorithms are evaluated qualitatively and quantitatively using three different data sets with comparative experiments, and the results show that the proposed methods are able to automatically detect, group, and label segments belonging to the same object classes. © 2008 IEEE.
Open Access
Ellipsoid genişletmeyle seyrek sinyal geri oluşturma
(IEEE, 2011-04) Gürbüz, A. C.; Pilancı, M.; Arıkan, Orhan
Bu makalede b = Ax + n şeklinde gürültülü A’nın tam rank ve x’in seyrek olduğu doğrusal bir denklem sistemi için seyrek x sinyallerini doğru olarak geri oluşturmaya yönelik yeni bir yöntem sunulmuştur. Önerilen yöntem kullanılan veri sınırını belirleyen ||Ax − b||2 = ellipsoidinin genişletilirken sırayla eksenlerin sıfırlanmasına dayanan yinelemeli bir yöntemdir. Seyrek sinyal oluşturma alanında yinelemeli ve 1 norm minimizasyon tabanlı standard yöntemlere göre benzer problemlerde daha yüksek başarım gösteren metot, eksik belirtilmiş sistemlerde standard metotların oluşturması gereken seyreklik seviyesini de yumuşatmaktadır
Open Access
Facile synthesis of cross-linked patchy fluorescent conjugated polymer nanoparticles by click reactions
(2011) İbrahimova, V.; Ekiz, S.; Gezici, Ö.; Tuncel, D.
Here, we report a novel method to synthesize multifunctional nanoparticles that can be used in biological studies, such as in cell imaging and as a carrier for biomolecules/drugs. The nanoparticles were prepared either via Cu-catalyzed or cucurbit[6]uril (CB6)-catalyzed click reactions between azide groups containing hydrophobic blue, green and yellow emitting fluorene-based conjugated polymers and a hydrophilic diaminodialkyne containing cross-linker. Through the click reaction, not only does the cross-linking confer stability, but it also introduces functional groups, such as triazoles and amines, to the nanoparticles. Moreover, CB6 not only acted as a catalyst to facilitate the copper-free click reaction, but it also allowed us to obtain nanoparticles containing rotaxanes in which the triazole units were encapsulated by CB6 units. TEM images of the nanoparticles also showed that they display very interesting morphologies. Incorporation of hydrophilic functional groups to the hydrophobic conjugated polymers resulted in a distinct phase separation, producing Janus-like or patchy particles.
Open Access
Imaging capability of pseudomorphic high electron mobility transistors, AlGaN/GaN, and Si micro-Hall probes for scanning Hall probe microscopy between 25 and 125 °c
(American Vacuum Society, 2009) Akram, R.; Dede, M.; Oral, A.
The authors present a comparative study on imaging capabilities of three different micro-Hall probe sensors fabricated from narrow and wide band gap semiconductors for scanning hall probe microscopy at variable temperatures. A novel method of quartz tuning fork atomic force microscopy feedback has been used which provides extremely simple operation in atmospheric pressures, high-vacuum, and variable-temperature environments and enables very high magnetic and reasonable topographic resolution to be achieved simultaneously. Micro-Hall probes were produced using optical lithography and reactive ion etching process. The active area of all different types of Hall probes were 1×1 μ m2. Electrical and magnetic characteristics show Hall coefficient, carrier concentration, and series resistance of the hall sensors to be 10 mG, 6.3× 1012 cm-2, and 12 k at 25 °C and 7 mG, 8.9× 1012 cm-2 and 24 k at 125 °C for AlGaNGaN two-dimensional electron gas (2DEG), 0.281 mG, 2.2× 1014 cm-2, and 139 k at 25 °C and 0.418 mG, 1.5× 1014 cm-2 and 155 k at 100 °C for Si and 5-10 mG, 6.25× 1012 cm-2, and 12 k at 25 °C for pseudomorphic high electron mobility transistors (PHEMT) 2DEG Hall probe. Scan of magnetic field and topography of hard disc sample at variable temperatures using all three kinds of probes are presented. The best low noise image was achieved at temperatures of 25, 100, and 125 °C for PHEMT, Si, and AlGaNGaN Hall probes, respectively. This upper limit on the working temperature can be associated with their band gaps and noise associated with thermal activation of carriers at high temperatures.
Open Access
An optimal network dimensioning and initial energy assignment minimizing the monetary cost of a heterogeneous WSN
(IEEE, 2009) Sevgi, Cüneyt; Kocyigit, A.
In this paper, a novel method is proposed to dimension a randomly deployed heterogeneous Wireless Sensor Network (WSN) of minimum monetary cost satisfying minimum coverage and minimum lifetime requirements. We consider WSNs consisting of two different types of nodes clusterheads and ordinary sensor nodes, randomly deployed over a sensing field. All devices are assumed to be stationary and have identical sensing capabilities. However, the clusterheads are more energetic and powerful in terms of processing and communication capabilities compared to sensor nodes. For such a network, finding minimum cost WSN problem is not a trivial one, since the distribution of the mixture of two different types of devices and the batteries with different initial energies in each type of device primarily determine the monetary cost of a WSN. Therefore, we formulated an optimization problem to minimize the monetary cost of a WSN for given coverage and lifetime requirements. The proposed optimization problem is solved for a certain scenario and the solution is validated by computer simulations. © 2009 IEEE.
Open Access
Three-dimensional motion and dense-structure estimation using convex projections
(SPIE, 1997-02) Alatan, A. Aydın; Erdem, A. Tanju; Onural, Levent
We propose a novel method for estimating the 3D motion and dense structure of an object form its two 2D images. The proposed method is an iterative algorithm based on the theory of projections onto convex sets (POCS) that involves successive projections onto closed convex constraint sets. We seek a solution for the 3D motion and structure information that satisfies the following constraints: (i) rigid motion - the 3D motion parameters are the same for each point on the object. (ii) Smoothness of the structure - depth values of the neighboring points on the object vary smoothly. (iii) Temporal correspondence - the intensities in the given 2D images match under the 3D motion and structure parameters. We mathematically derive the projection operators onto these sets and discuss the convergence properties of successive projections. Experimental results show that the proposed method significantly improves the initial motion and structure estimates.
Open Access
Video based fire detection at night
(IEEE, 2009) Taşdemir, Kasım; Günay, Osman; Töreyin, Behçet Uğur; Çetin, A. Enis
There has been increasing interest in the study of video based fire detection as video based surveillance systems become widely available for indoor and outdoor monitoring applications. Video based fire detection methods in computer vision literature do not take into account whether the fire takes place in the day time or at night. A novel method explicitly developed for video based detection of fire at night (in the dark) is presented in this paper. The method comprises three sub-algorithms each of which characterizes certain part of fire at night. Individual decisions of the sub-algorithms are combined together using a least-mean-square based decision fusion approach.
Open Access
VOC gas leak detection using pyro-electric infrared sensors
(IEEE, 2010) Erden, Fatih; Soyer, E. B.; Toreyin, B. U.; Çetin, A. Enis
In this paper, we propose a novel method for detecting and monitoring Volatile Organic Compounds (VOC) gas leaks by using a Pyro-electric (or Passive) Infrared (PIR) sensor whose spectral range intersects with the absorption bands of VOC gases. A continuous time analog signal is obtained from the PIR sensor. This signal is discretized and analyzed in real time. Feature parameters are extracted in wavelet domain and classified using a Markov Model (MM) based classifier. Experimental results are presented. ©2010 IEEE.