• 한국컴퓨터정보학회논문지
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• 제21권5호
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• pp.31-40
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• 2016

In this paper, we analyse the characteristics of the edge image and propose a new entropy coding optimized to the compression of the edge image. The pixel values of the edge image have the Gaussian distribution around '0', and most of the pixel values are '0'. By using this analysis, the Zero Block technique is utilized in spatial domain. And the Intra Prediction Mode of the edge image is similar to the mode of the surrounding blocks or likely to be the Planar Mode or the Horizontal Mode. In this paper, we make use of the MPM technique that produces the Intra Prediction Mode with high probability modes. By utilizing the above properties, we design a new entropy coding method that is suitable for edge image and perform the compression. In case the existing compression techniques are applied to edge image, compression ratio is low and the algorithm is complicated as more than necessity and the running time is very long, because those techniques are based on the natural images. However, the compression ratio and the running time of the proposed technique is high and very short, respectively, because the proposed algorithm is optimized to the compression of the edge image. Experimental results indicate that the proposed algorithm provides better visual and PSNR performance up to 11 times than the JPEG.

• 전자공학회논문지T
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• 제36T권3호
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• pp.32-40
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• 1999

본 논문에서는 SEA (successive elimination algorithm) 기반의 고속 블록정합 움직임 추정 알고리즘을 제시한다. 제안하는 기법은 블록 움직임 벡터가 탐색영역의 중앙에 편향되어 분포한다는 특성에 기반 하여 기존의 SEA보다 탐색영역에서 탐색점의 수를 줄임으로써 성능을 향상시키는 기법이다. 또한 더 많은 연산량을 즐기기 위하여 제안된 기법은 블록정합에서 화소를 비교하는 연산량을 줄이는 RBMAD (reduced bits mean absolute difference) 정합기준과 블록정합에서 사용되는 화소의 수를 줄이는 부표본화 기법과 결합하였다. 제안된 기법은 완전탐색 (full-search, FS) 블록정합 알고리즘과 비슷한 성능을 유지하면서 기존의 고속 알고리즘보다 성능이 향상되었음을 실험을 통하여 확인하였다

• Journal of applied mathematics & informatics
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• 제26권3_4호
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• pp.661-672
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• 2008

In this paper an algorithm, based on extracting a certain target of an image, is proposed that is capable of performing bilevel thresholding of image with multimodal distribution. Each pixel in the image has a membership value which is used to denote the characteristic relationship between the pixel and its belonging region (i.e. the object or background). Using the membership values of image set, a new measurement, which simultaneously measures the measure of fuzziness and the conditional entropy of the image, is calculated. Then, thresholds are found by optimally minimizing calculated measurement. In addition, a fuzzy range is defined to improve the threshold values. The experimental results demonstrate that the proposed approach can select the thresholds automatically and effectively extract the meaningful target from the input image. The resulting image can preserve the object region we target very well.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2006년도 추계학술대회 논문집 Vol.19
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• pp.286-287
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• 2006

Electrowetting display (EWD) is one of the strong candidates for electronic paper like display (EPD). However, in the conventional EWD, the oil movement occurs in random direction so that we can observe irregular distribution of contracted oil in the operation. To realize colorful display and achieve a fast response time, oil movement in the pixel should be directed in a specific direction. In this paper, we report the result of oil contraction with specified direction which is achieved by patterned electrode. From the experiments, we find that the oil movement depends on the portion of etched electrode area and study other influencing factors of patterned electrode on the oil movement.

• Journal of Information Technology Applications and Management
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• 제12권1호
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• pp.231-239
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• 2005

This paper describes a new algorithm for pixel-based skin color detection to differentiate human form in color images by the ratio of R to H. In order to detect skin color efficiently, we examine the distribution of the R, G and B color elements combining to constitute the skin color in various color images. It shows that R is located in a narrower area than G and B on the RGB color space. And skin color is more related to R than G and B. Meanwhile, when the color image is transformed to the HSI color space, the S is variously changed in accordance with skin colors. The I is changed in accordance with the quantity and angle of light. But the H is less influenced by other conditions except for color. On the basis of the aforementioned study, we propose that the threshold for skin color detection is decided by the ratio of R to H. The proposed method narrows down the range of threshold, detects more skin color and reduces mis-detection of skin color in comparison to detection by R or H. In experimentation. it shows that the proposed algorithm overcomes changes of brightness and color to detect skin color in color images.

• 한국의학물리학회지:의학물리
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• 제15권3호
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• pp.128-133
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• 2004

기능적 자기공명영상을 이용하여 진동자의 자극에 따른 감각 피질의 반응에 대하여 연구하였다 주로 40 Hz 이하의 주파수에 반응하는 촉각소체의 혈류반응을 조사하기 위하여 8, 15, 그리고 25 Hz의 주파수를 사용하였다. 사용되고 있는 진동자의 한계를 극복한 공기의 압력을 이용하여 진동할 수 있는 진동자를 특수 제작하였다. 예측한 바와 같이 감각 피질의 촉각소체 부위가 주파수에 따라 반응하는 모습을 볼 수 있었다. 주파수 대 반응 면적을 각 pixel의 개수와 signal percent change로 분석하여 주파수가 증가할수록 signal percent change의 분포는 넓어지고 더 많은 pixel들이 반응한다는 것을 알 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권1호
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• pp.360-373
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• 2017

This paper presents a novel digital video steganalysis scheme against the spatial domain video steganography technology based on a spatial temporal detector (ST_D) that considers both spatial and temporal redundancies of the video sequences simultaneously. Three descriptors are constructed on XY, XT and YT planes respectively to depict the spatial and temporal relationship between the current pixel and its adjacent pixels. Considering the impact of local motion intensity and texture complexity on the histogram distribution of three descriptors, each frame is segmented into non-overlapped blocks that are $8{\times}8$ in size for motion and texture analysis. Subsequently, texture and motion factors are introduced to provide reasonable weights for histograms of the three descriptors of each block. After further weighted modulation, the statistics of the histograms of the three descriptors are concatenated into a single value to build the global description of ST_D. The experimental results demonstrate the great advantage of our features relative to those of the rich model (RM), the subtractive pixel adjacency model (SPAM) and subtractive prediction error adjacency matrix (SPEAM), especially for compressed videos, which constitute most Internet videos.

• 한국컴퓨터정보학회논문지
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• 제11권1호
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• pp.63-69
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• 2006

언제 어디서나 네트워크에 연결되어 있는 유비쿼터스 환경에서의 무선 단말기의 컨텐츠에 대한 연구가 활성화되고 있다. 본 논문에서는 일반 컴퓨터의 인터넷 컨텐츠를 무선 단말기를 이용하여 얻을 수 있도록 하는 프레임워크를 제안하고자 한다. 프레임워크의 컨텐츠를 관리하는 서버의 성능 향상을 위해서 다수의 리소스 중에서 위한 중요 이미지를 선정하고, 선정된 이미지만을 단말기에서 재생 가능한 이미지로 변환하는 것이 본 논문의 목표이다. 이를 위해 웹 문서의 이미지 관련 정보 중 화면 표시율(DPR)과 이미지의 분포 영역을 고려하여 다수의 변환 요구 이미지 중에서 중요 이미지를 선별한 후 모바일 이미지로 변환 서비스하여 서버의 모바일 이미지로의 변환 시간 및 자원을 축소 시켜 서버의 성능을 향상시키고자 한다.

• 대한공간정보학회지
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• 제11권2호
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• pp.11-16
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• 2003

강우에 의한 토양유실은 환경에 심각한 영향을 미치고 있음에도 불구하고, 인식의 부족으로 실제 유역에서 발생되고 있는 유실량을 측정한 자료가 없는 실정이다. 본 연구에서는 GSIS와의 연계가 가능하고 일반적으로 사용할 있는 USLE 모형을 선정하여 토양유실량 예측에 이용하였으며, 모형에 입력되는 인자들을 GSIS 공간분석 기능을 이용하여 추출하였다. 특히 USLE 모형을 다소 수정하여 유역에 적용할 수 있도록 하였으며, 산불전과 후의 토양유실량을 계산하여 토지피복변화가 토양유실량에 미치는 영향을 분석하였다. 격자크기를 22m로 구성하여 격자별 침식량을 확인할 수 있어 토양유실량 분포현황을 파악할 수 있었다.

• 제어로봇시스템학회논문지
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• 제16권3호
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• pp.269-276
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• 2010

In this paper, we present the detection method of moving objects based on two background models. These background models support to understand multi layered environment belonged in images taken by shaking camera and each model is MBM(Multiple Background Model) and TMBM (Temporal Median Background Model). Because two background models are Pixel-based model, it must have noise by camera movement. Therefore correlation coefficient calculates the similarity between consecutive images and measures camera motion vector which indicates camera movement. For the calculation of correlation coefficient, we choose the selected region and searching area in the current and previous image respectively then we have a displacement vector by the correlation process. Every selected region must have its own displacement vector therefore the global maximum of a histogram of displacement vectors is the camera motion vector between consecutive images. The MBM classifies the intensity distribution of each pixel continuously related by camera motion vector to the multi clusters. However, MBM has weak sensitivity for temporal intensity variation thus we use TMBM to support the weakness of system. In the video-based experiment, we verify the presented algorithm needs around 49(ms) to generate two background models and detect moving objects.