• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.9
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• pp.95-103
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• 1998

This paper proposes an image segmentation algorithm based on fusion of range and intensity images. Based on Bayesian theory, a priori knowledge is encoded by the Markov random field (MRF). A maximum a posteriori (MAP) estimator is constructed using the features extracted from range and intensity images. Objects are approximated by local planar surfaces in range images, and the parametric space is constructed with the surface parameters estimated pixelwise. In intensity images the ${\alpha}$-trimmed variance constructs the intensity feature. An image is segmented by optimizing the MAP estimator that is constructed using a likelihood function based on edge information. Computer simulation results shw that the proposed fusion algorithm effectively segments the images independentl of shadow, noise, and light-blurring.

• Progress in Superconductivity
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• v.11 no.2
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• pp.118-122
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• 2010

Electrical transport properties were measured on $SmFeAsO_{0.85}$ single crystals along the c-axis for various temperatures and magnetic fields. For the measurements a mesa structure was fabricated on the surface of the single crystals. Samples showed a metallic temperature dependence of resistance and current-voltage curves without hysteretic multiple branch splitting that is usually observed in tunneling Josephson junctions. In addition, in ab-planar magnetic fields, samples did not show the Fraunhofer-type field modulation of the critical current. All these features indicate that the c-axis transport characteristics of $SmFeAsO_{0.85}$ single crystals are explained by the anisotropic bulk superconductivity rather than Josephson tunneling.

• Smart Structures and Systems
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• v.5 no.3
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• pp.291-316
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• 2009

Damage detection using structural classical deflection flexibility has received considerable attention due to the unique features of the flexibility in the last two decades. However, for relatively complex structures, most methods based on classical deflection flexibility fail to locate damage sites to the exact members. In this study, for structures whose members are dominated by axial forces, such as truss structures, a more feasible flexibility for damage detection is proposed, which is called the Axial Strain (AS) flexibility. It is synthesized from measured modal frequencies and axial strain mode shapes which are expressed in terms of translational mode shapes. A damage indicator based on AS flexibility is proposed. In addition, how to integrate the AS flexibility into the Damage Location Vector (DLV) approach (Bernal and Gunes 2004) to improve its performance of damage localization is presented. The methods based on AS flexbility localize multiple damages to the exact members and they are suitable for the cases where the baseline data of the intact structure is not available. The proposed methods are demonstrated by numerical simulations of a 14-bay planar truss and a five-story steel frame and experiments on a five-story steel frame.

• International Journal of CAD/CAM
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• v.9 no.1
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• pp.37-46
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• 2010

Existing methods for the registration of blurred images are efficient for the artificially blurred images or a planar registration, but not suitable for the naturally blurred images existing in the real image mosaic process. In this paper, we attempt to resolve this problem and propose a method for a distortion-free stitching of naturally blurred images for image mosaic. It adopts a multi-resolution and robust feature based inter-layer mosaic together. In each layer, Harris corner detector is chosen to effectively detect features and RANSAC is used to find reliable matches for further calibration as well as an initial homography as the initial motion of next layer. Simplex and subspace trust region methods are used consequently to estimate the stable focal length and rotation matrix through the transformation property of feature matches. In order to stitch multiple images together, an iterative registration strategy is also adopted to estimate the focal length of each image. Experimental results demonstrate the performance of the proposed method.

• Electronics and Telecommunications Trends
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• v.36 no.3
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• pp.12-22
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• 2021

Since the technical realization of self-aligned planar complementary metal-oxide-semiconductor field-effect transistors in 1960s, semiconductor manufacturing has aggressively pursued scaling that fruitfully resulted in tremendous advancement in device performances and realization of features sizes smaller than 10 nm. Due to many intrinsic material and technical obstacles, continuing the scaling progress of semiconductor devices has become increasingly arduous. As an effort to circumvent the areal limit, stacking devices in a three-dimensional fashion has been suggested. This approach is commonly called monolithic three-dimensional (M3D) integration. In this work, we examined technical issues that need to be addressed and overcome to fully realize energy efficiency, short latency and cost competency. Full-fledged M3D technologies are expected to contribute to various new fields of artificial intelligence, autonomous gadgets and unknowns, which are to be discovered.

• Communications for Statistical Applications and Methods
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• v.31 no.3
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• pp.309-322
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• 2024

Identifying algae in water is important for managing algal blooms which have great impact on drinking water supply systems. There have been various microscopic approaches developed for algae classification. Many of them are based on the morphological features of algae. However, there have seldom been mathematical frameworks for comparing the shape of algae, represented as a planar continuous curve obtained from an image. In this work, we describe a recent framework for computing shape distance between two different algae based on the elastic metric and a novel functional representation called the square root velocity function (SRVF). We further introduce statistical procedures for multiple shapes of algae including computing the sample mean, the sample covariance, and performing the principal component analysis (PCA). Based on the shape distance, we classify six algal species in watersheds experiencing algal blooms, including three cyanobacteria (Microcystis, Oscillatoria, and Anabaena), two diatoms (Fragilaria and Synedra), and one green algae (Pediastrum). We provide and compare the classification performance of various distance-based and model-based methods. We additionally compare elastic shape distance to non-elastic distance using the nearest neighbor classifiers.

• Journal of Oral Medicine and Pain
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• v.30 no.1
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• pp.107-119
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• 2005

Temporomandibular joint arthritides is divided into osteoarthritis, osteoarthrosis and polyarthritis. Because the signs, symptoms and radiographical features of osteoarthritis and osteoarthrosis are similar without arthralgia, diffenential diagnosis is difficult. Also non-radiographically change in early Osteoarthritis leads to misdiagnose. Planar bone scan and SPECT are useful to detect bone change early. This study was carried out in order to make diagnostic criteria of planar bone scan and SPECT. Three hundred and four temporomandibular joints were examined with clinical examination, computerized tomograph, planar bone scan, and SPECT. The obtained results were as follows. 1. If temporomandibular joint simple uptake ratio of patient in twenties is over 1.397%, it's condition may be osteoarthritis. And simple uptake ratio over in thirties-fourties may mean osteoarthritis. 2. It may mean osteoarthritis of temporomandibular joint that the number of coronal and transverse SPECT frame with hot spot is over four. 3. Destructive stage may goes on, if simple uptake ratio is over 1.370% in tweenties and over 1.104% in thirties-fourties. 4. If the number of coronal SPECT frame with hot spot is over four, temporomandibular joint may be on destructive stage in tweenties, thirties-fourties. And if the number of transverse SPECT frame with hot spot is over three, it may be on destructive stage in all ages. 5. When patient complains subjective arthralgia and palpation arthralgia, bone change may be more active than each arthralgia. 6. Osteoarthritis may progress gradually worse in 4.5 anamnesis. And then it may be stable gradually and turn to osteoarthrosis.

• Journal of Broadcast Engineering
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• v.21 no.1
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• pp.36-42
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• 2016

Recently, many 3D contents have been produced through the multiview camera system. In this system, since a difference of the viewpoint between color and depth cameras is inevitable, the camera parameter plays the important role to adjust the viewpoint as a preprocessing step. The conventional camera calibration method is inconvenient to users since we need to choose pattern features manually after capturing a planar chessboard with various poses. Therefore, we propose a semi-auto camera calibration method using a circular sampling and an homography estimation. Firstly, The proposed method extracts the candidates of the pattern features from the images by FAST corner detector. Next, we reduce the amount of the candidates by the circular sampling and obtain the complete point cloud by the homography estimation. Lastly, we compute the accurate position having the sub-pixel accuracy of the pattern features by the approximation of the hyper parabola surface. We investigated which factor affects the result of the pattern feature detection at each step. Compared to the conventional method, we found the proposed method released the inconvenience of the manual operation but maintained the accuracy of the camera parameters.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.49-58
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• 2011

Typically, vision-based AR systems operate on the basis of prior knowledge of the environment such as a square marker. The traditional marker-based AR system has a limitation that the marker has to be located in the sensing range. Therefore, there have been considerable research efforts for the techniques known as real-time camera tracking, in which the system attempts to add unknown 3D features to its feature map, and these then provide registration even when the reference map is out of the sensing range. In this paper, we describe a real-time camera tracking framework specifically designed to track a monocular camera in a desktop workspace. Basic idea of the proposed scheme is that a real-time camera tracking is achieved on the basis of a plane tracking algorithm. Also we suggest a method for re-detecting features to maintain registration of virtual objects. The proposed method can cope with the problem that the features cannot be tracked, when they go out of the sensing range. The main advantage of the proposed system are not only low computational cost but also convenient. It can be applicable to an augmented reality system for mobile computing environment.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.1
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• pp.111-121
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• 2006

Recently, many studies have been performed to apply airborne LIDAR data to extracting urban models. In order to model efficiently the man-made objects which are the main components of these urban models, it is important to extract automatically planar patches from the set of the measured three-dimensional points. Although some research has been carried out for their automatic extraction, no method published yet is sufficiently satisfied in terms of the accuracy and completeness of the segmentation results and their computational efficiency. This study thus aimed to developing an efficient approach to automatic segmentation of planar patches from the three-dimensional points acquired by an airborne LIDAR system. The proposed method consists of establishing adjacency between three-dimensional points, grouping small number of points into seed patches, and growing the seed patches into surface patches. The core features of this method are to improve the segmentation results by employing the variable threshold value repeatedly updated through a statistical analysis during the patch growing process, and to achieve high computational efficiency using priority heaps and sequential least squares adjustment. The proposed method was applied to real LIDAR data to evaluate the performance. Using the proposed method, LIDAR data composed of huge number of three dimensional points can be converted into a set of surface patches which are more explicit and robust descriptions. This intermediate converting process can be effectively used to solve object recognition problems such as building extraction.