• KIEAE Journal
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• 제3권2호
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• pp.59-66
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• 2003

To be the design method supporting aesthetic ability of human, CAAD system should essentially recognize architectural form in the same way of human. In this study, visual perception process of human was analyzed to search proper computational method performing similar step of perception of it. Through the analysis of visual perception, vision was separated to low-level vision and high-level vision. Edge detection and neural network were selected to model after low-level vision and high-level vision. The 24 images of building, tree and landscape were processed by edge detection and trained by neural network. And 24 new images were used to test trained network. The test shows that trained network gives right perception result toward each images with low error rate. This study is on the meaning of artificial intelligence in design process rather than on the design automation strategy through artificial intelligence.

• 한국축산식품학회:학술대회논문집
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• 한국축산식품학회 2006년도 정기총회 및 제37차 춘계 국제학술발표대회
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• pp.325-328
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• 2006

In low nitrite level, treatment of combined with pressure and thermal processing improved cured meat colour comparing with that of only thermal processing. However, visual colour of only pressurised treatment could not be improved at low nitrite level. Pressure treatment could develop cured meat colour when high nitrite level was added. Moreover, pressurisation combined with thermal processing decreased nitrite residuals compared to thermal processing. Therefore the results indicated that pressurisation combined with thermal processing had potential benefits in appearance of cured meat products, promising improved food safety.

• 제어로봇시스템학회논문지
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• 제9권8호
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• pp.640-646
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• 2003

We presents an edge-based point correlation algorithm for fast and stable visual inspection system. Conventional algorithms based on NGC(normalized gray-level correlation) have to overcome some difficulties in applying automated inspection systems to real factory environment. First of all, NGC algorithms involve highly complex computation and thus require high performance hardware for realtime process. In addition, lighting condition in realistic factory environments is not stable and therefore intensity variation from uncontrolled lights gives many troubles for applying NGC directly as pattern matching algorithm. We propose an algorithm to solve these problems, using thinned and binarized edge data, which are obtained from the original image. A point correlation algorithm with the thinned edges is introduced with image pyramid technique to reduce the computational complexity. Matching edges instead of using original gray-level image pixels overcomes problems in NGC method and pyramid of edges also provides fast and stable processing. All proposed methods are proved by the experiments using real images.

• 전자공학회논문지S
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• 제34S권4호
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• pp.25-32
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• 1997

In this paper, we propose an adaptive BTC algorithm using the characteristics of the error signals. The BTC algorithm has a avantage that it is low computational complexity, but a disadvantage that it produces the ragged edges in the reconstructed images for th esloping regions beause of coding the input with 2-level signals. Firstly, proposed methods classify the input into low, medium, and high activity blocks based on the variance of th einput. Using 1-level quantizer for low activity block, 2-level for medium, and 4-level for high, it is adaptive methods that reduce bit rates and the inherent quantization noises in the 2-level quantizer. Also, in case of processing high activity block, we propose a new quantization level allocation algorithm using the characteristics of the error signals between the original signals and the reconstructed signals used by 2-level quantizer, in oder that reduce bit rates superior to the conventional 4-level quantizer. Especially, considering the characteristics of input block, we reduce the bit rates without incurrng the visual noises.

• 정보처리학회논문지B
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• 제13B권2호
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• pp.121-126
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• 2006

본 논문에서는 웹 이미지의 분류 효과를 높이기 위해 이미지 자체에서 추출된 저수준의 비주얼 특징뿐만 아니라 이미지와 관련된 텍스트 정보로부터 나온 고수준 시맨틱 특징들을 이용하는 분류 방법을 제안한다. 이 고수준의 텍스트 특징들은 이미지 URL, 파일명, 페이지 타이틀, 하이퍼링크 및 이미지 주변 텍스트로부터 얻어진다. 분류 엔진으로는 Kohonen의 SOM(Self Organizing Map)을 사용한다. 고수준의 텍스트 특징들과 저수준의 비주얼 특징들을 동시에 사용하는 SOM 기반의 이미지 분류에서는 10개의 카테고리로부터 수집된 200개의 테스트 이미지들이 사용되었다. 분류 성능을 평가하기 위해 간단하면서도 새로운 두 가지 척도, 즉 동일 카테고리 이미지들의 산포 정도와 집적 정도를 나타내는 각각의 척도를 정의하고 사용하였다. 실험결과, SOM기반의 웹 이미지 분류에서는 고수준의 텍스트 특징들이 보다 유용한 것임이 밝혀졌다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.610-615
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• 2005

Visual servoing is the fusion of results from many elemental areas including high-speed image processing, kinematics, dynamics, control theory, and real-time computing. It has much in common with research into active vision and structure from motion, but is quite different from the often described use of vision in hierarchical task-level robot control systems. We present a new approach to visual feedback control using image-based visual servoing with the stereo vision in this paper. In order to control the position and orientation of a robot with respect to an object, a new technique is proposed using a binocular stereo vision. The stereo vision enables us to calculate an exact image Jacobian not only at around a desired location but also at the other locations. The suggested technique can guide a robot manipulator to the desired location without giving such priori knowledge as the relative distance to the desired location or the model of an object even if the initial positioning error is large. This paper describes a model of stereo vision and how to generate feedback commands. The performance of the proposed visual servoing system is illustrated by the simulation and experimental results and compared with the case of conventional method for dual-arm robot made in Samsung Electronics Co., Ltd.

• 핵의학기술
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• 제12권1호
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• pp.13-18
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• 2008

목적: 다양한 algorism에 의한 영상처리기법은 핵의학 영상을 결정짓는 중요한 부분을 차지하고 있다. 이에 새로운 영상처리기법인 SIEMENS (made by pixon)사의 Onco. flash processing reconstruction을 적용하여 기존의 영상처리기법을 이용한 영상과 비교 분석함으로써 그 임상적 유용성을 평가한다. 대상 및 방법: 1) Scan speed의 차이에 의한 whole body bone scan을 시행하고, raw data와 processing data의 imaeg quality를 비교 분석하여 상대 평가한다. 2) Bone static scan을 acquisition count를 달리하여 시행하고, raw data와 processing data의 image quality를 비교 분석하여 상대 평가한다. 3) 4 quadrant - bar phantom을 이용하여 raw data와 processing data와의 육안적 평가를 통한 image quality를 확인한다. 4) LSF을 통한 raw data와 processing data의 FWHM을 구하여 해상력 평가를 확인한다. 결과: 1) Whole body bone scan을 시행하여 본원 핵의학 판독의의 blinding test한 결과 scan speed 20 cm/min의 raw data와 30 cm/min의 processing data에는 임상 판독에 영향을 미칠 수준의 image quality 저하가 없었으나, 40 cm/min processing data는 영상 판독과 진단에 오류의 가능성을 배제 할 수 없는 image quality의 향상을 볼 수 없었다. 2) Bone static scan의 경우 200 kcts processing data는 200 kcts raw data보다 확실한 image quality의 향상을 가져왔으며 400 kcts raw data와 비교한 본원 핵의학 판독의 blinding test 결과 판독과 진단에 무리가 없을 수준의 유사한 image quality를 보였다. 3) 4 quadrant - bar phantom을 이용하여 raw data와 processing data와의 육안적 평가는 processing을 통한 image quality의 향상을 확인할 수 있었다. 4) LSF을 통한 raw data와 processing data의 FWHM 평가 결과, resolution의 뚜렷한 증가나 감소의 확인은 할 수 없었다. 이는 noise level의 감소와 high S/N ratio 때문이라 판단된다. 결론: 기존의 영상과 비교 분석하여 평가한 결과 Onco. flash processing reconstruction을 적용한 경우 일정 수준까지 뚜렷한 image quality의 향상을 보였으며, 이는 장비 가동률의 상승과 환자 대기일수의 단축 그리고 저선량 검사에 따른 방사선 피폭에 대한 적극적 방어의 관점에서 현재 임상 핵의학에 충분한 유용성과 타당성이 있을 것으로 사료된다.

• ETRI Journal
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• 제29권3호
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• pp.353-362
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• 2007

In this paper, we propose a novel unsupervised video object extraction algorithm for individual images or image sequences with low depth of field (DOF). Low DOF is a popular photographic technique which enables the representation of the photographer's intention by giving a clear focus only on an object of interest (OOI). We first describe a fast and efficient scheme for extracting OOIs from individual low-DOF images and then extend it to deal with image sequences with low DOF in the next part. The basic algorithm unfolds into three modules. In the first module, a higher-order statistics map, which represents the spatial distribution of the high-frequency components, is obtained from an input low-DOF image. The second module locates the block-based OOI for further processing. Using the block-based OOI, the final OOI is obtained with pixel-level accuracy. We also present an algorithm to extend the extraction scheme to image sequences with low DOF. The proposed system does not require any user assistance to determine the initial OOI. This is possible due to the use of low-DOF images. The experimental results indicate that the proposed algorithm can serve as an effective tool for applications, such as 2D to 3D and photo-realistic video scene generation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권10호
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• pp.3591-3606
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• 2014

In this paper, a robust watermarking scheme is proposed that uses the scale-invariant feature transform (SIFT) algorithm in the discrete wavelet transform (DWT) domain. First, the SIFT feature areas are extracted from the original image. Then, one level DWT is applied on the selected SIFT feature areas. The watermark is embedded by modifying the fractional portion of the horizontal or vertical, high-frequency DWT coefficients. In the watermark extracting phase, the embedded watermark can be directly extracted from the watermarked image without requiring the original cover image. The experimental results showed that the proposed scheme obtains the robustness to both signal processing and geometric attacks. Also, the proposed scheme is superior to some previous schemes in terms of watermark robustness and the visual quality of the watermarked image.

• ETRI Journal
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• 제39권1호
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• pp.97-107
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• 2017

A fast and accurate building-level visual place recognition method built on an image-retrieval scheme using street-view images is proposed. Reference images generated from street-view images usually depict multiple buildings and confusing regions, such as roads, sky, and vehicles, which degrades retrieval accuracy and causes matching ambiguity. The proposed practical database refinement method uses informative reference image and keypoint selection. For database refinement, the method uses a spatial layout of the buildings in the reference image, specifically a building-identification mask image, which is obtained from a prebuilt three-dimensional model of the site. A global-positioning-system-aware retrieval structure is incorporated in it. To evaluate the method, we constructed a dataset over an area of $0.26km^2$. It was comprised of 38,700 reference images and corresponding building-identification mask images. The proposed method removed 25% of the database images using informative reference image selection. It achieved 85.6% recall of the top five candidates in 1.25 s of full processing. The method thus achieved high accuracy at a low computational complexity.