• The Journal of Korea Robotics Society
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• v.12 no.1
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• pp.33-41
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• 2017

We present a region-based approach for accurate pose estimation of small mechanical components. Our algorithm consists of two key phases: Multi-view object co-segmentation and pose estimation. In the first phase, we explain an automatic method to extract binary masks of a target object captured from multiple viewpoints. For initialization, we assume the target object is bounded by the convex volume of interest defined by a few user inputs. The co-segmented target object shares the same geometric representation in space, and has distinctive color models from those of the backgrounds. In the second phase, we retrieve a 3D model instance with correct upright orientation, and estimate a relative pose of the object observed from images. Our energy function, combining region and boundary terms for the proposed measures, maximizes the overlapping regions and boundaries between the multi-view co-segmentations and projected masks of the reference model. Based on high-quality co-segmentations consistent across all different viewpoints, our final results are accurate model indices and pose parameters of the extracted object. We demonstrate the effectiveness of the proposed method using various examples.

• Journal of Korea Multimedia Society
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• v.20 no.1
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• pp.43-50
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• 2017

According to living environment, the number of deaths due to thyroid diseases increased. In this paper, we proposed an algorithm for recognizing a thyroid detection using texture analysis based on shape, gray level co-occurrence matrix and gray level run length matrix. First of all, we segmented the region of interest (ROI) using active contour model algorithm. Then, we applied a total of 18 features (5 first order descriptors, 10 Gray level co-occurrence matrix features(GLCM), 2 Gray level run length matrix features and shape feature) to each thyroid region of interest. The extracted features are used as statistical analysis. Our results show that first order statistics (Skewness, Entropy, Energy, Smoothness), GLCM (Correlation, Contrast, Energy, Entropy, Difference variance, Difference Entropy, Homogeneity, Maximum Probability, Sum average, Sum entropy), GLRLM features and shape feature helped to distinguish thyroid benign and malignant. This algorithm will be helpful to diagnose of thyroid nodule on ultrasound images.

• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.41-47
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• 2009

A solution to the problems of recognizing as one spot or detection failures for complex regions, in which many spots representing proteins are overlapped and saturated, is suggested. The accumulated gradients of each point in complex regions are calculated, and the resulting accumulated gradient image segmented using watershed technique. The suggested solution show better and efficient result than existing method for spot separation, detects more protein spots hidden in the image of 2-dimensional electrophoresis, and expands the scope of prediction.

• Geomechanics and Engineering
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• v.37 no.2
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• pp.189-195
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• 2024

Buried pipelines can be classified as continuous and segmented pipelines. These infrastructures can be damaged either by ground movement or by seismic wave propagation during an earthquake. Permanent ground deformations (PGD) include surface faulting, liquefaction-induced lateral spreading and landslide. Liquefaction is a major problem for both superstructures and infrastructures. Buyukcekmece lake zone, which is the studied region in this paper, is a liquefaction prone area located near the North Anatolian Fault Line. It is an active fault line in Turkey and a major earthquake with a magnitude of around 7.5 is expected in this investigated region in Istanbul. It is planned to be constructed a new 12" steel natural gas pipeline from one side of the lake to the other side. In this study, this case has been examined in terms of two different support conditions. Firstly, it has been defined as a beam in liquefied soil and has built-in supports at both ends. In the other approach, this case has been modeled as a beam in liquefied soil and has vertical elastic pinned supports at both ends. These models have been examined and some solution proposals have been produced according to the obtained results. In this study, based on this sample, it is aimed to determine the behaviors of buried continuous pipelines subject to liquefaction effects in terms of buoyancy.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.1
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• pp.17-24
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• 2024

Recently, retail technology has been developed by the rapid evolution of e-commerce and a representative example is ESL technology. In this study, we investigate ESL technology, market status and forecasts, and analyze the competitive structure between relational companies. Market analysis refers to data from market reports of Marketsandmarkets and Research, and internet media. In ESL, the display field is predicted to account for 43% of the total market in 2026, and is converting from LCD to electronic paper. The segmented type is becoming more advanced into the full-graphic type, and CAGR of 18.7% for 3-7 inches and 20.6% for 7-10 inches is predicted. The demand for ESL is greatest in North America and Europe, but CAGR is the highest in the Asia-Pacific region at 19.1%. Since ESL technology has a lot of overlap with semiconductor and display technology, the Asia-Pacific region is relatively advantageous, and this has led to rapid growth of domestic companies. However, it is expected that competition from European companies that are actually owned by Chinese companies will increase in the future, so continuous technological development and new market development are necessary.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12C
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• pp.1147-1153
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• 2009

We propose a novel image segmentation and segment-based stereo matching technique using color, depth, and motion information. Proposed technique firstly splits reference images into foreground region or background region using depth information from depth camera. Then each region is segmented into small segments with color information. Moreover, extracted segments in current frame are tracked in the next frame in order to maintain depth consistency between frames. The initial depth from the depth camera is also used to set the depth search range for stereo matching. Proposed segment-based stereo matching technique was compared with conventional one without foreground and background separation and other conventional one without motion tracking of segments. Simulation results showed that the improvement of segment extraction and depth estimation consistencies by proposed technique compared to conventional ones especially at the static background region.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.810-813
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• 2004

Indexing and Retrieving images from large and varied collections using image content as a key is a challenging and important problem in computer vision application. In this paper, a color Content-based Image Retrieval (CBIR) system using hierarchical Region of Interest (ROI) query and indexing is presented. During indexing process, First, The ROIs on every image in the image database are extracted using a region-based image segmentation technique, The JSEG approach is selected to handle this problem in order to create color-texture regions. Then, Color features in form of histogram and correlogram are then extracted from each segmented regions. Finally, The features are stored in the database as the key to retrieve the relevant images. As in the retrieval system, users are allowed to select ROI directly over the sample or user's submission image and the query process then focuses on the content of the selected ROI in order to find those images containing similar regions from the database. The hierarchical region-of-interest query is performed to retrieve the similar images. Two-level search is exploited in this paper. In the first level, the most important regions, usually the large regions at the center of user's query, are used to retrieve images having similar regions using static search. This ensures that we can retrieve all the images having the most important regions. In the second level, all the remaining regions in user's query are used to search from all the retrieved images obtained from the first level. The experimental results using the indexing technique show good retrieval performance over a variety of image collections, also great reduction in the amount of searching time.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.593-601
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• 2016

This paper is related to the Region-based Spectral Correlation Estimation(RSCE) coding method that makes it possible to achieve the high-compression ratio by estimating color component images from luminance image. The proposed method is composed of three steps. First, Y/C bit-plane summation image is defined using normalized chrominance summation image and luminance image, and then the Y/C bit-plane summation image is segmented for extracting the shape information of the regions. Secondly, the scale factor and the offset factor minimizing the approximation square errors between luminance image and R, B images by the each region are calculated. Finally, the scale factor and the offset factor for the each region are encoded into bit stream. Referring to the results of computer simulation, the proposed method provides more than two or three times higher compression ratio than JPEG/Baseline or JPEG2000/EBCOT algorithm in terms of bpp needed for encoding two color component images with the same PSNR.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.411-420
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• 2004

We propose a novel still image compression system, which is superior in its function than the JPEG2000 system developed by David Taubman. The system shows 40 : 1 high compression ratio using $2\times2$ bitmatrix subblock coding. The $2\times2$ bitmatrix subblock is constructed in the bitplanes by organizing the bits into subblocks composing of $2\times2$matrices. The arithmetic coding performs the high compression by the bitmatrices in the subblock. The input of the system consists of a segmentation mode and a ROI(Region Of Interest) mode. In segmentation mode, the input image is segmented into a foreground consisting of letters and a background consisting of the remaining region. In ROI mode, the input image is represented by the region of interest window. The high compression ratio shows that the proposed system is competent among the JPEG2000 products currently in the market. This system also uses gray coding to improve the compression ratio.

• Journal of Korea Multimedia Society
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• v.16 no.10
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• pp.1135-1146
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• 2013

In this paper, we proposed a new algorithm for individual tooth region segmentation on tooth color images. The proposed algorithm used oral cavity model based on structural feature of tooth and new boundary of watershed algorithm. First, the gray scale image is obtained with emphasized tooth regions from the color images and unnecessary regions are removed on tooth images. Next, the image enhancement of tooth images is implemented using the proposed oral cavity model, and the individual tooth regions are segmented by watershed algorithm on the enhanced images. Boundary and seeds necessary to watershed algorithm are applied boundary of binary image using minimum thresholding and region maximum value. In order to evaluate performance of proposed algorithm, we conduct experiment to compare conventional algorithm with proposed algorithm. As a result of experiment, we confirmed that the proposed algorithm is more improved detection ratio than conventional algorithm at molar regions and the tooth region detection performance is improved by preventing overlap detection on oral cavity.