• Journal of Korea Multimedia Society
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• v.15 no.5
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• pp.569-576
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• 2012

This paper presents an x-ray medical image panorama system which can overcome the smallness of the images that exist on a source computer during remote medical processing. In the system, after the standard medical image format DICOM is converted to the PC standard image format, a MSR algorithm is used to enhance X-ray images of low quality. Then SURF and Multi-band blending are applied to generate a panoramic image. Also, this paper evaluates the proposed SURF based system through the average gray value error and image quality criterion with X-ray image data by comparing with a SIFT based system. The results show that the proposed system is superior to SIFT based system in image quality.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.1005-1007
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• 2017

문화적 진보와 경제 발전은 사람들의 사회 활동을 증가시키고 있으며, 이로 인하여 사람들이 자신에게 적합한 옷을 착용하고자 하는 요구가 높아졌다. 이러한 현상에 따라 일일이 매장을 방문하여 옷을 구입하는 것보다는 가상현실(또는 증강현실)내에서 다양한 옷을 입어보고자 하는 Virtual Dressing Room에 대한 연구개발이 많이 수행되어 왔다. 본 논문에서는 이러한 증강현실 기술을 기반으로 하는 Virtual Dressing 시스템에 대하여 제시한다. 특히 그 간에 수행되지 않았던 장애인을 위한 Virtual Dressing 시스템을 SURF 알고리즘을 기반으로 제시한다. 이러한 시스템은 움직임이 불편한 장애인에게 더욱 필수적인 시스템이 될 것이며, 인터넷 기반의 매장을 위해 수요도 충족할 것으로 판단한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.96-98
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• 2018

요즘 많은 사람이 사용하고 있는 쏘카, 그린카, 피플카, 딜카 등 카 셰어링(car sharing) 애플리케이션 방식에 대한 차량 외관 부분이 많은 문제점으로 발생하고 있다. 본 논문에서는 기존의 카 셰어링 시스템에 SURF(Speed-Up Robust Feature) 시스템 방식을 휴대폰 애플리케이션에 적용하여 카 셰어링 시스템에서 발생하고 있는 외부적인 훼손에 대하여 사용자들의 안정적인 보안 솔루션을 제공하고자 한다.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.67-72
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• 2019

This paper proposes a computer vision-based banknote recognition system intended to assist the blind. This system is robust and fast in recognizing banknotes on videos recorded with a smartphone on real-life scenarios. To reduce the computation time and enable a robust recognition in cluttered environments, this study segments the banknote candidate area from the background utilizing a technique called Pixel-Based Adaptive Segmenter (PBAS). The Speeded-Up Robust Features (SURF) interest point detector is used, and SURF feature vectors are computed only when sufficient interest points are found. The proposed algorithm achieves a recognition accuracy of 98%, a 100% true recognition rate and a 0% false recognition rate. Although Korean banknotes are used as a working example, the proposed system can be applied to recognize other countries' banknotes.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.1
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• pp.35-41
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• 2012

This paper proposes a moving object detection algorithm for active camera system that can be applied to mobile robot and intelligent surveillance system. Most of moving object detection algorithms based on a stationary camera system. These algorithms used fixed surveillance system that does not consider the motion of the background or robot tracking system that track pre-learned object. Unlike the stationary camera system, the active camera system has a problem that is difficult to extract the moving object due to the error occurred by the movement of camera. In order to overcome this problem, the motion of the camera was compensated by using SURF and Pseudo Perspective model, and then the moving object is extracted efficiently using stochastic Label Cluster transport model. This method is possible to detect moving object because that minimizes effect of the background movement. Our approach proves robust and effective in terms of moving object detection in active camera system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.11a
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• pp.133-136
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• 2011

본 논문에서는 SURF 알고리즘을 이용한 직교식 스테레오 카메라 영상의 칼라 불균형 보정 방법 제안한다. 제안 방법에서는 SURF 알고리즘을 이용하여 스테레오 좌, 우 영상의 대응점을 찾은 후, 찾은 대응점들의 칼라 보정 벡터를 영상 획득 모델을 기반으로 계산한다. 영상 전체에서 다양한 칼라 대응점 정보를 추출하기 위하여 본 논문에서는 분할영상을 이용하여 칼라 대응점 정보를 추출한다. 추출된 대응점 정보는 초기 칼라 보정 벡터로 변환할 수 있으며 좌, 우 영상의 모든 픽셀에 대하여 색정보가 가장 유사한 대응점의 보정 벡터를 사용하여 칼라 불균형을 보정한다. 초기 보정 벡터를 이용한 칼라 불균형 보정 후 존재하는 노이즈을 제거하기 위하여 유사한 색공간에 위치한 칼라 보정 벡터에 가우시안 필터를 적용한다. 실험 결과로 원본 영상과 보정된 영상의 칼라 히스토그램을 비교하였으며, 분할 영역의 수에 따른 보정 결과도 비교 제시하였다. 실험 결과는 제안한 방법이 직교식 스테레오 카메라 영상에 효과적인 칼라 불균형 보정 방법임을 보여준다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.4
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• pp.961-968
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• 2015

As BIM has been increasingly applied to building project recently, its application to civil engineering project is also on the rise. As construction structures have been expanded and complicated in a size and type, the information for handling maintenance process has also increased. Thus, to actively utilize the BIM information created at the design stage, this study has been carried out to establish a maintenance system using a marker-less based augmented reality method, by presenting a maintenance system for the construction structures using augmented reality. A SURF algorithm is used to link the 3D objects in the design and construction phases to the maintenance phase. The presented method in this study can increase the utilization of 3D information created at the design stage, by offering an augmented reality technology at the maintenance stage. The method could also improve the efficiency of visual inspection on construction structures by augmenting 3D model of a bridge structure.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.57-64
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• 2013

In this paper, we propose the classification method of medicine bottle images using the features with color and size information. It is difficult to classify with size feature only, because there are many similar sizes of bottles. Therefore, we suggest a classification method based on color information, which robust to illumination variations. First, we extract MBR(Minimum Boundary Rectangle) of medicine bottle area using Binary Threshold of Red, Green, and Blue in image and classify images with size. Then, hue information and RGB color average rate are used to classify image, which features are robust to lighting variations. Finally, using SURF(Speed Up Robust Features) algorithm, corresponding image can be found from candidates with previous extracted features. The proposed method makes to reduce execution time and minimize the error rate and is confirmed to be reliable and efficient from experiment.

• Journal of Internet Computing and Services
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• v.20 no.4
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• pp.55-61
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• 2019

In this paper, if images are acquired in all-time situations through various sensors (EO/IR, SAR, GMTI, LiDAR) used for defense purposes, the images can be analyzed and expressed in augmented reality(AR). Various algorithms are used to process images with augmented reality, and depending on the situation, it is necessary to decide which algorithms to select and use. Through the performance comparison (error rate, processing time, accuracy) of SIFT, SURF, ORB, and BRISK, the representative augmented reality algorithm, it is analyzed and proposed which augmented reality algorithm is effective to use under various situations in the defense field.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.3
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• pp.162-168
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• 2013

This paper examines the implementation of automatic compensation modules for digital camera image when a person is closing his/her eyes. The modules detect the face and eye region and then recognize the eye state. If the image is taken when a person is closing his/her eyes, the function corrects the eye and produces the image by using the most satisfactory image of the eye state among the past frames stored in the buffer. In order to recognize the face and eye precisely, the pre-process of image correction is carried out using SURF algorithm and Homography method. For the detection of face and eye region, Haar-like feature algorithm is used. To decide whether the eye is open or not, similarity comparison method is used along with template matching of the eye region. The modules are tested in various facial environments and confirmed to effectively correct the images containing faces.