• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2109-2123
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• 2017

This paper presents a super-resolution reconstruction method based on sparse representation for two-dimensional bar code images. Considering the features of two-dimensional bar code images, Kirsch and LBP (local binary pattern) operators are used to extract the edge gradient and texture features. Feature extraction is constituted based on these two features and additional two second-order derivatives. By joint dictionary learning of the low-resolution and high-resolution image patch pairs, the sparse representation of corresponding patches is the same. In addition, the global constraint is exerted on the initial estimation of high-resolution image which makes the reconstructed result closer to the real one. The experimental results demonstrate the effectiveness of the proposed algorithm for two-dimensional bar code images by comparing with other reconstruction algorithms.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1887-1890
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• 2003

This paper presents a three-dimensional (3D) head pose estimation algorithm using the stereo image. Given a pair of stereo image, we automatically extract several important facial feature points using the disparity map, the gabor filter and the canny edge detector. To detect the facial feature region , we propose a region dividing method using the disparity map. On the indoor head & shoulder stereo image, a face region has a larger disparity than a background. So we separate a face region from a background by a divergence of disparity. To estimate 3D head pose, we propose a 2D-3D Error Compensated-SVD (EC-SVD) algorithm. We estimate the 3D coordinates of the facial features using the correspondence of a stereo image. We can estimate the head pose of an input image using Error Compensated-SVD (EC-SVD) method. Experimental results show that the proposed method is capable of estimating pose accurately.

• Journal of Multimedia Information System
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• v.4 no.2
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• pp.79-82
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• 2017

Smoke and fire have different shapes and colours. This article suggests a fully connected system which is used two features using Adaboost algorithm for constructing a strong classifier as linear combination. We calculate the local histogram feature by gradient and bin, local binary pattern value, and projection vectors for each cell. According to the histogram magnitude, this paper applied adapted weighting value to improve the recognition rate. To preserve the local region and shape feature which has edge intensity, this paper processed the normalization sequence. For the extracted features, this paper Adaboost algorithm which makes strong classification to classify the objects. Our smoke detection system based on the proposed approach leads to higher detection accuracy than other system.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.321-322
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• 1998

In this paper, a medical images retrieval method using feature extraction based on wavelet transform is proposed. We used energy of coefficients which is represented by wavelet transform. The proposed retrieval algorithm is comprised of the two retrieval. At first, we make a energy map for wavelet coefficient of a query image and then compare is to one of db image. And then we use an edge information of the query image to retrieve the images selected at the first retrieval once more. Consequently some retrieved images are displayed on screen.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5506-5521
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• 2017

Three-dimensional video (3DV), as the new generation of video format standard, can provide the viewers with a vivid screen sense and a realistic stereo impression. Meanwhile the view synthesis has become an important issue for 3DV application. Differently from the conventional methods based on depth, in this paper we propose a new view synthesis algorithm, which can employ the correlation among views and warp in the image domain only. There are mainly two contributions. One is the incorporation of sobel edge points into feature extraction and matching, which can obtain a better stable homography and then a visual comfortable synthesis view compared to SIFT points only. The other is a novel image blending method proposed to obtain a better synthesis image. Experimental results demonstrate that the proposed method can improve the synthesis quality both in subjectivity and objectivity.

• 한국IT서비스학회:학술대회논문집
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• 2003.05a
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• pp.623-628
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• 2003

제품의 개발 및 생산 과정에는 설계, 해석, 가공, 검사 등의 많은 부문이 서로 밀접하게 연계되어 있고 각 부문 간에는 각기 서로 다른 형태의 정보를 필요로 하기 때문에 이들의 유기적인 통합을 위해서는 각각의 응용 분야에서 요구되는 다양한 정보가 효과적으로 제공될 필요가 있다. 본 연구에서는 특징형상을 이용하여 설계 기능과 다른 응용 부분을 유기적으로 연계할 수 있는 알고리즘을 제시한다. ISO에서 진행 중인 STEP의 Form Feature을 기준으로 일반적인 분류를 하고 이를 기초로 특징형상을 인식하고자 하였다. 이를 위해 B-Rep 데이터로부터 Face-Edge Graph를 구성하고 다중 절점(Cut Node)을 인식하였으며, 본 연구를 바탕으로 하여 향후 몇 가지 단점을 보완하고 대상 영역을 확대시켜 감으로써 Computer-aided Design 시스템으로부터 얻어지는 3차원 형상 데이터로부터 Computer-aided Process Plan을 위해 필요한 특징형상을 컴퓨터에 의해 자동으로 추출하기 위한 발판을 구축할 수 있을 것이다.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.40-47
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• 2010

This paper presents a simultaneous localization and mapping (SLAM) of an indoor hallway environment using Rao-Blackwellized particle filter (RBPF) along with a line segment as a landmark. Based on the fact that fluent line features can be extracted around the ceiling and side walls of hallway using vision sensor, a horizontal line segment is extracted from an edge image using Hough transform and is also tracked continuously by an optical flow method. A successive observation of a line segment gives initial state of the line in 3D space. For data association, registered feature and observed feature are matched in image space through a degree of overlap, an orientation of line, and a distance between two lines. Experiments show that a compact environmental map can be constructed with small number of horizontal line features in real-time.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.3
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• pp.465-472
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• 2015

This paper presents a visual touch recognition for NUI(Natural User Interface) using Voronoi-tessellation algorithm. The proposed algorithms are three parts as follows: hand region extraction, hand feature point extraction, visual-touch recognition. To improve the robustness of hand region extraction, we propose RGB/HSI color model, Canny edge detection algorithm, and use of spatial frequency information. In addition, to improve the accuracy of the recognition of hand feature point extraction, we propose the use of Douglas Peucker algorithm, Also, to recognize the visual touch, we propose the use of the Voronoi-tessellation algorithm. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.18 no.1
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• pp.60-65
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• 2015

We report a pediatric patient admitted with abdominal pain, diffuse lower extremity edema and watery diarrhea for two months. Laboratory findings including complete blood count, serum albumin, lipid and immunoglobulin levels were compatible with protein losing enteropathy. Colonoscopic examination revealed diffuse ulcers with smooth raised edge (like "punched out holes") in the colon and terminal ileum. Histopathological examination showed active colitis, ulcerations and inclusion bodies. Immunostaining for cytomegalovirus was positive. Despite supportive management, antiviral therapy, the clinical condition of the patient worsened and developed disseminated cytomegalovirus infection and the patient died. Protein losing enteropathy and disseminated cytomegalovirus infection a presenting of feature in steroid-naive patient with inflammatory bowel disease is very rare. Hypogammaglobulinemia associated with protein losing enteropathy in Crohn's disease may predispose the cytomegalovirus infection in previously healthy children.

• Journal of the Semiconductor & Display Technology
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• v.17 no.3
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• pp.113-116
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• 2018

This paper proposes a mobile image search system which uses a sensor information of smart phone, and enables running in a variety of environments, which is implemented on Android platform. The implemented system deals with a new image descriptor using combination of the visual feature (CEDD) with EXIF attributes in the target of JPEG image, and image matching scheme, which is optimized to the mobile platform. Experimental result shows that the proposed method exhibited a significant improved searching results of around 80% in precision in the large image database. Considering the performance such as processing time and precision, we think that the proposed method can be used in other application field.