• Title/Summary/Keyword: Coordinate Estimation

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Estimation of Illuminant Chromaticity by Equivalent Distance Reference Illumination Map and Color Correlation (균등거리 기준 조명 맵과 색 상관성을 이용한 조명 색도 추정)

  • Kim Jeong Yeop
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.6
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    • pp.267-274
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    • 2023
  • In this paper, a method for estimating the illuminant chromaticity of a scene for an input image is proposed. The illuminant chromaticity is estimated using the illuminant reference region. The conventional method uses a certain number of reference lighting information. By comparing the chromaticity distribution of pixels from the input image with the chromaticity set prepared in advance for the reference illuminant, the reference illuminant with the largest overlapping area is regarded as the scene illuminant for the corresponding input image. In the process of calculating the overlapping area, the weights for each reference light were applied in the form of a Gaussian distribution, but a clear standard for the variance value could not be presented. The proposed method extracts an independent reference chromaticity region from a given reference illuminant, calculates the characteristic values in the r-g chromaticity plane of the RGB color coordinate system for all pixels of the input image, and then calculates the independent chromaticity region and features from the input image. The similarity is evaluated and the illuminant with the highest similarity was estimated as the illuminant chromaticity component of the image. The performance of the proposed method was evaluated using the database image and showed an average of about 60% improvement compared to the conventional basic method and showed an improvement performance of around 53% compared to the conventional Gaussian weight of 0.1.

New Fast Block-Matching Motion Estimation using Temporal and Spatial Correlation of Motion Vectors (움직임 벡터의 시공간 상관성을 이용한 새로운 고속 블럭 정합 움직임 추정 방식)

  • 남재열;서재수;곽진석;이명호;송근원
    • Journal of Broadcast Engineering
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    • v.5 no.2
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    • pp.247-259
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    • 2000
  • This paper introduces a new technique that reduces the search times and Improves the accuracy of motion estimation using high temporal and spatial correlation of motion vector. Instead of using the fixed first search Point of previously proposed search algorithms, the proposed method finds more accurate first search point as to compensating searching area using high temporal and spatial correlation of motion vector. Therefore, the main idea of proposed method is to find first search point to improve the performance of motion estimation and reduce the search times. The proposed method utilizes the direction of the same coordinate block of the previous frame compared with a block of the current frame to use temporal correlation and the direction of the adjacent blocks of the current frame to use spatial correlation. Based on these directions, we compute the first search point. We search the motion vector in the middle of computed first search point with two fixed search patterns. Using that idea, an efficient adaptive predicted direction search algorithm (APDSA) for block matching motion estimation is proposed. In the experimental results show that the PSNR values are improved up to the 3.6dB as depend on the Image sequences and advanced about 1.7dB on an average. The results of the comparison show that the performance of the proposed APDSA algorithm is better than those of other fast search algorithms whether the image sequence contains fast or slow motion, and is similar to the performance of the FS (Full Search) algorithm. Simulation results also show that the performance of the APDSA scheme gives better subjective picture quality than the other fast search algorithms and is closer to that of the FS algorithm.

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Study on Queue Length Estimation using GPS Trajectory Data (GPS 데이터를 이용한 대기행렬길이 산출에 관한 연구)

  • Lee, Yong-Ju;Hwang, Jae-Seong;Lee, Choul-Ki
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.15 no.3
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    • pp.45-51
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    • 2016
  • Existing real-time signal control system was brought up typical problems which are supersaturated condition, point detection system and loop detection system. For that reason, the next generation signal control system of advanced form is required. Following thesis aimed at calculating queue length for the next generation signal control system to utilize basic parameter of signal control in crossing queue instead of the volume of real-time through traffic. Overflow saturated condition which was appeared as limit of existing system was focused to set-up range. Real-time location information of individual vehicle which is collected by GPS data. It converted into the coordinate to apply shock wave model with an linear equation that is extracted by regression model applied by a least square. Through the calculated queue length and link length by contrast, If queue length exceed the link, queue of downstream intersection is included as queue length that upstream queue vehicle is judeged as affecting downstream intersection. In result of operating correlation analysis among link travel time to judge confidence of extracted queue length, Both of links were shown over 0.9 values. It is appeared that both of links are highly correlated. Following research is significant using real-time data to calculate queue length and contributing to signal control system.

Auto-Segmentation Algorithm For Liver-Vessel From Abdominal MDCT Image (복부 MDCT 영상으로부터 간혈관 자동 추출 알고리즘)

  • Park, Seong-Me;Lee, You-Jin;Park, Jong-Won
    • Journal of Korea Multimedia Society
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    • v.13 no.3
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    • pp.430-437
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    • 2010
  • It is essential for living donor liver transplantation that surgeon must understand the hepatic vessel structure to improve the success rate of operation. In this paper, we extract the liver boundary without other surrounding structures such as heart, stomach, and spleen using the contrast enhanced MDCT liver image sequence. After that, we extract the major hepatic veins (left, middle, right hepatic vein) with morphological filter after review the basic structure of hepatic vessel which reside in segmented liver image region. The purpose of this study is provide the overall status of transplantation operation with size estimation of resection part which is dissected along with the middle hepatic vein. The method of liver extraction is as follows: firstly, we get rid of background and muscle layer with gray level distribution ratio from sampling process. secondly, the coincident images match with unit mesh image are unified with resulted image using the corse coordinate of liver and body. thirdly, we extract the final liver image after expanding and region filling. Using the segmented liver images, we extract the hepatic vessels with morphological filter and reversed the major hepatic vessels only with a results of ascending order of vessel size. The 3D reconstructed views of hepatic vessel are generated after applying the interpolation to provide the smooth view. These 3D view are used to estimate the dissection line after identify the middle hepatic vein. Finally, the volume of resection region is calculated and we can identify the possibility of successful transplantation operation.

Vehicle Headlight and Taillight Recognition in Nighttime using Low-Exposure Camera and Wavelet-based Random Forest (저노출 카메라와 웨이블릿 기반 랜덤 포레스트를 이용한 야간 자동차 전조등 및 후미등 인식)

  • Heo, Duyoung;Kim, Sang Jun;Kwak, Choong Sub;Nam, Jae-Yeal;Ko, Byoung Chul
    • Journal of Broadcast Engineering
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    • v.22 no.3
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    • pp.282-294
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    • 2017
  • In this paper, we propose a novel intelligent headlight control (IHC) system which is durable to various road lights and camera movement caused by vehicle driving. For detecting candidate light blobs, the region of interest (ROI) is decided as front ROI (FROI) and back ROI (BROI) by considering the camera geometry based on perspective range estimation model. Then, light blobs such as headlights, taillights of vehicles, reflection light as well as the surrounding road lighting are segmented using two different adaptive thresholding. From the number of segmented blobs, taillights are first detected using the redness checking and random forest classifier based on Haar-like feature. For the headlight and taillight classification, we use the random forest instead of popular support vector machine or convolutional neural networks for supporting fast learning and testing in real-life applications. Pairing is performed by using the predefined geometric rules, such as vertical coordinate similarity and association check between blobs. The proposed algorithm was successfully applied to various driving sequences in night-time, and the results show that the performance of the proposed algorithms is better than that of recent related works.

Verification of Stereotactic Target Point Achieved by Acquisition of MR Image in Actual Treatment Position of Radiosurgery (정위적 방사선 수술시 치료위치에서의 정위적 표적점 확인을 통한 자기공명영상 획득의 정확도 연구)

  • 윤형근;신교철;김영식
    • Progress in Medical Physics
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    • v.9 no.2
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    • pp.89-94
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    • 1998
  • To make practical application of the MR image for stereotactic radiosurgery, the target point-achieved by acquisition of MR image in stereotactic radiosurgery planning system must agree with the actual isocenter of irradiation in real treatment. And the amount of distortion of the MR image must be known to make a correction for the agreement. A radish containing abundant water content was chosen as a homogeneous phantom for the purpose of verification of the agreement in this experiment. A dosimetric film was firmly attached to the small specially fabricated acryl plate and needle puncture was made through the film just into the acryl plate and a drop of oil was dropped into the hole of the film. The acryl plate with film was inserted into the radish and the dorp of oil represented the target point in MR image. After the image acquisition by stereotatic radiosurgery planning system, we achieved stereotactic coordinate of the target point represented by the oil drop. And we proceeded to actual irradiation to the target point according to the procedure of stereotactic radiosurgery. After the irradiation, the film in the radish was developed and processed and the degree of coincidence between the center of the radiation distribution and the target point represented by the hole in the film was measured. The discrepancy between two points was under 0.5 mm. so we could confirm good coincidence in homogeneous phantom such as radish. On the other hand, authors tried to use our home-made device for estimation of distortion of MR image.

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A Prediction Search Algorithm by using Temporal and Spatial Motion Information from the Previous Frame (이전 프레임의 시공간 모션 정보에 의한 예측 탐색 알고리즘)

  • Kwak, Sung-Keun;Wee, Young-Cheul;Kimn, Ha-Jine
    • Journal of the Korea Computer Graphics Society
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    • v.9 no.3
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    • pp.23-29
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    • 2003
  • There is the temporal correlation of the video sequence between the motion vector of current block and the motion vector of the previous block. If we can obtain useful and enough information from the motion vector of the same coordinate block of the previous frame, the total number of search points used to find the motion vector of the current block may be reduced significantly. In this paper, we propose the block-matching motion estimation using an adaptive initial search point by the predicted motion information from the same block of the previous frame. And the first search point of the proposed algorithm is moved an initial point on the location of being possibility and the searching process after moving the first search point is processed according to the fast search pattern. Simulation results show that PSNR(Peak-to-Signal Noise Ratio) values are improved UP to the 1.05dB as depend on the image sequences and improved about 0.33~0.37dB on an average. Search times are reduced about 29~97% than the other fast search algorithms. Simulation results also show that the performance of the proposed scheme gives better subjective picture quality than the other fast search algorithms and is closer to that of the FS(Full Search) algorithm.

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Compensation Method for Occluded-region of Arbitrary-view Image Synthesized from Multi-view Video (다시점 동영상에서 임의시점영상 생성을 위한 가려진 영역 보상기법)

  • Park, Se-Hwan;Song, Hyuk;Jang, Eun-Young;Hur, Nam-Ho;Kim, Jin-Woong;Kim, Jin-Soo;Lee, Sang-Hun;Yoo, Ji-Sang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.12C
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    • pp.1029-1038
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    • 2008
  • In this paper, we propose a method for an arbitrary-view image generation in multi-view video and methods for pre- and post-processing to compensate unattended regions in the generated image. To generate an arbitrary-view image, camera geometry is used. Three dimensional coordinates of image pixels can be obtained by using depth information of multi-view video and parameter information of multi-view cameras, and by replacing three dimensional coordinates on a two dimensional image plane of other view, arbitrary-view image can be reconstructed. However, the generated arbitrary-view image contains many unattended regions. In this paper, we also proposed a method for compensating these regions considering temporal redundancy and spatial direction of an image and an error of acquired multi-view image and depth information. Test results show that we could obtain a reliably synthesized view-image with objective measurement of PSNR more than 30dB and subjective estimation of DSCQS(double stimulus continuous quality scale method) more than 3.5 point.

AdaBoost-based Gesture Recognition Using Time Interval Window Applied Global and Local Feature Vectors with Mono Camera (모노 카메라 영상기반 시간 간격 윈도우를 이용한 광역 및 지역 특징 벡터 적용 AdaBoost기반 제스처 인식)

  • Hwang, Seung-Jun;Ko, Ha-Yoon;Baek, Joong-Hwan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.3
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    • pp.471-479
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    • 2018
  • Recently, the spread of smart TV based Android iOS Set Top box has become common. This paper propose a new approach to control the TV using gestures away from the era of controlling the TV using remote control. In this paper, the AdaBoost algorithm is applied to gesture recognition by using a mono camera. First, we use Camshift-based Body tracking and estimation algorithm based on Gaussian background removal for body coordinate extraction. Using global and local feature vectors, we recognized gestures with speed change. By tracking the time interval trajectories of hand and wrist, the AdaBoost algorithm with CART algorithm is used to train and classify gestures. The principal component feature vector with high classification success rate is searched using CART algorithm. As a result, 24 optimal feature vectors were found, which showed lower error rate (3.73%) and higher accuracy rate (95.17%) than the existing algorithm.

Mobile Camera-Based Positioning Method by Applying Landmark Corner Extraction (랜드마크 코너 추출을 적용한 모바일 카메라 기반 위치결정 기법)

  • Yoo Jin Lee;Wansang Yoon;Sooahm Rhee
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1309-1320
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    • 2023
  • The technological development and popularization of mobile devices have developed so that users can check their location anywhere and use the Internet. However, in the case of indoors, the Internet can be used smoothly, but the global positioning system (GPS) function is difficult to use. There is an increasing need to provide real-time location information in shaded areas where GPS is not received, such as department stores, museums, conference halls, schools, and tunnels, which are indoor public places. Accordingly, research on the recent indoor positioning technology based on light detection and ranging (LiDAR) equipment is increasing to build a landmark database. Focusing on the accessibility of building a landmark database, this study attempted to develop a technique for estimating the user's location by using a single image taken of a landmark based on a mobile device and the landmark database information constructed in advance. First, a landmark database was constructed. In order to estimate the user's location only with the mobile image photographing the landmark, it is essential to detect the landmark from the mobile image, and to acquire the ground coordinates of the points with fixed characteristics from the detected landmark. In the second step, by applying the bag of words (BoW) image search technology, the landmark photographed by the mobile image among the landmark database was searched up to a similar 4th place. In the third step, one of the four candidate landmarks searched through the scale invariant feature transform (SIFT) feature point extraction technique and Homography random sample consensus(RANSAC) was selected, and at this time, filtering was performed once more based on the number of matching points through threshold setting. In the fourth step, the landmark image was projected onto the mobile image through the Homography matrix between the corresponding landmark and the mobile image to detect the area of the landmark and the corner. Finally, the user's location was estimated through the location estimation technique. As a result of analyzing the performance of the technology, the landmark search performance was measured to be about 86%. As a result of comparing the location estimation result with the user's actual ground coordinate, it was confirmed that it had a horizontal location accuracy of about 0.56 m, and it was confirmed that the user's location could be estimated with a mobile image by constructing a landmark database without separate expensive equipment.