• Title/Summary/Keyword: Depth image error

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Method for Determining Variable-Block Size of Depth Picture for Plane Coding (깊이 화면의 평면 부호화를 위한 가변 블록 크기 결정 방법)

  • Kwon, Soon-Kak;Lee, Dong-Seok
    • Journal of Korea Society of Industrial Information Systems
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    • v.22 no.3
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    • pp.39-47
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    • 2017
  • The Depth Picture can be Encoded by the Plane Coding Mode that is the Method for Coding Mode by Considering a Part of the Picture as the Plane. In this Paper, we Propose the Method of Determining the Variable-sized Block for Variable Block Coding in the Plane Coding Mode for the Depth Picture. The Depth Picture Can be Encoded in the Plane Coding Through Estimating the Plane Which is Close to Pixels in the Block Using Depth Information. The Variable-sized Block Coding in the Plane Coding can be Applied as Follows. It Calculates the Prediction Error between Predicted Depths by the Plane Estimation and the Measured Depths. If Prediction Error is Below the Threshold, the Block is Encoded by Current Size. Otherwise, it Divides the Block and Repeats Above. If the Block is Divided Below the Minimum Size, the Block is not Encoded by the Plane Coding Mode. The Result of the Simulation of the Proposed Method Shows that the Number of Encoded Block is Reduced to 19% as Compared with the Method Using the Fixed-sized Block in the Depth Picture Composed of one Plane.

The Measurement of the Depth of Crack using Images of SLAM (SLAM 영상을 이용한 크랙 깊이 측정)

  • Hwang, Ki-Hwan;Jun, Kye-Suk
    • The Journal of the Acoustical Society of Korea
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    • v.16 no.3
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    • pp.51-56
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    • 1997
  • In this paper, we studied the configuration and depth measurement method of the crack in the interior of solid with scanning laser acoustic microscope. Precision measurement method of crack depth is required in SLAM because that system reconstructs the shadow image to the transmission coefficient. We proposed this method that used geometrical structure to the shadow area of SLAM images obtained from oblique incidence and the mode conversion of ultrasound in specimen and then experimented it. For this experiment, we fabricated various specimens which had the vertical line-crack with different depth and made the wedge as 20$^{\circ}$ for oblique incidence. Experimental results showed that the shadow area of SLAM images were proportional to the depth of crack. Measured depth error to the crack was less than 6% compared with practical crack depth.

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Depth Measurement Method Robust against Scattering of Line Lasers (라인 레이저의 산란에 강인한 심도 측정 방법)

  • Ko, Kwangjin;Yeon, Sungho;Kim, Jaemin
    • Journal of Korea Multimedia Society
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    • v.21 no.2
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    • pp.181-187
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    • 2018
  • Line-laser beams are used for depth measurement of welding beads along the circumference of a pipe. For this, first we project a line-laser beam on an rotating pipe and take a sequence of images of the beam projected on the pipe using a CCD camera. Second, the projected line laser beam in each image is detected, converted into a thin curve. Finally measure the distance between the thinned curve and an imaginary line. When a line-laser beam is projected to a rough metal surface such as arc welding beads, the beam is severely scattered. This severe scattering makes the thinned curve perturbed. In this paper, we propose a thinning method robust against scattering of line lasers. First, we extract a projected line laser beam region using an adaptive threshold. Second, we model a thinned curve with a spline curve with control points. Next, we adjust the control points to fit the curve to the projected line-laser beam. Finally, we take a weighted mean of thin curves on a sequence of image frames. Experiments shows that the proposed thinning method results in a thinning curve, which is smooth and fit to the projected line-laser beam with small error.

Quantifying Chloride Ingress in Cracked Concrete Using Image Processing (이미지 분석을 이용한 균열 콘크리트 내 염화물 침투 정량화 평가)

  • Kim, Kun-Soo;Park, Ki-Tae;Kim, Jaehwan
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.26 no.4
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    • pp.57-64
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    • 2022
  • Chloride, which is one of the main deterioration factors in reinforced concrete structures, can degrade the performance of the structure due to chloride-induced corrosion of steel. Chloride content at steel depth or the rate of chloride penetration is necessary to determine deterioration of reinforced concrete or to calculate initiation time of steel corrosion caused by chloride attack. Chlorides in concrete are generally identified with typical two methods including chloride profiling using potentiometric titration method and discoloration method using AgNO3 solution. The former is advantageous to estimate chloride penetration rate (diffusion coefficient in general) with measured chloride contents directly, but it is laborious. In the case of latter, while the result is obtained easily with the range of discoloration, the error may occur depending on workmanship when the depth of chloride ingress is measured. This study shows that chloride penetrated depth is evaluated with the results obtained from discoloration method through image analysis, thereby the error is minimized by workmanship. In addition, the effect of micro-crack in concrete is studied on chloride penetration. In conclusion, the depth of chloride penetration was quantified with image analysis and as it was confirmed that chlorides can rapidly penetrate through micro-cracks, caution is especially required for cracks in concrete structure.

A Study on the Mean Flow Velocity Distribution of Jeju Gangjung-Stream using ADCP (ADCP를 활용한 제주 강정천의 평균유속 분포 추정)

  • Yang, Se-Chang;Kim, Yong-Seok;Yang, Sung-Kee;Kang, Myung-Soo;Kang, Bo-Seong
    • Journal of Environmental Science International
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    • v.26 no.9
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    • pp.999-1011
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    • 2017
  • In this study, the Chiu-2D velocity-flow rate distribution based on theoretical background of the entropy probability method was applied to actual ADCP measurement data of Gangjung Stream in Jeju from July 2011 to June 2015 to predict the parameter that take part in velocity distribution of the stream. In addition, surface velocity measured by SIV (Surface Image Velocimeter) was applied to the predicted parameter to calculate discharge. Calculated discharge was compared with observed discharge of ADCP observed during the same time to analyze propriety and applicability of depth of water velocity average conversion factor. To check applicability of the predicted stream parameter, surface velocity and discharge were calculated using SIV and compared with velocity and flow based on ADCP. Discharge calculated by applying velocity factor of SIV to the Chiu-2D velocity-flow rate distribution and discharge based on depth of water velocity average conversion factor of 0.85 were $0.7171m^3/sec$ and $0.5758m^3/sec$, respectively. Their error rates compared to average ADCP discharge of $0.6664m^3/sec$ were respectively 7.63% and 13.64%. Discharge based on the Chiu-2D velocity-flow distribution showed lower error rate compared to discharge based on depth of water velocity average conversion factor of 0.85.

Development of Computer Vision System for Individual Recognition and Feature Information of Cow (II) - Analysis of body parameters using stereo image - (젖소의 개체인식 및 형상 정보화를 위한 컴퓨터 시각 시스템 개발(II) - 스테레오 영상을 이용한 체위 분석 -)

  • 이종환
    • Journal of Biosystems Engineering
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    • v.28 no.1
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    • pp.65-76
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    • 2003
  • The analysis of cow body parameters is important to provide some useful information fur cow management and cow evaluation. Present methods give many stresses to cows because they are invasive and constrain cow postures during measurement of body parameters. This study was conducted to develop the stereo vision system fur non-invasive analysis of cow body features. Body feature parameters of 16 heads at two farms(A, B) were measured using scales and nineteen stereo images of them with walking postures were captured under outdoor illumination. In this study, the camera calibration and inverse perspective transformation technique was established fer the stereo vision system. Two calibration results were presented for farm A and fm B, respectively because setup distances from camera to cow were 510 cm at farm A and 630cm at farm B. Calibration error values fer the stereo vision system were within 2 cm for farm A and less than 4.9 cm for farm B. Eleven feature points of cow body were extracted on stereo images interactively and five assistant points were determined by computer program. 3D world coordinates for these 15 points were calculated by computer program and also used for calculation of cow body parameters such as withers height. pelvic arch height. body length. slope body length. chest depth and chest width. Measured errors for body parameters were less than 10% for most cows. For a few cow. measured errors for slope body length and chest width were more than 10% due to searching errors fer their feature points at inside-body positions. Equation for chest girth estimated by chest depth and chest width was presented. Maximum of estimated error fur chest girth was within 10% of real values and mean value of estimated error was 8.2cm. The analysis of cow body parameters using stereo vision system were successful although body shape on the binocular stereo image was distorted due to cow movements.

Human hand gesture identification framework using SIFT and knowledge-level technique

  • Muhammad Haroon;Saud Altaf;Zia-ur- Rehman;Muhammad Waseem Soomro;Sofia Iqbal
    • ETRI Journal
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    • v.45 no.6
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    • pp.1022-1034
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    • 2023
  • In this study, the impact of varying lighting conditions on recognition and decision-making was considered. The luminosity approach was presented to increase gesture recognition performance under varied lighting. An efficient framework was proposed for sensor-based sign language gesture identification, including picture acquisition, preparing data, obtaining features, and recognition. The depth images were collected using multiple Microsoft Kinect devices, and data were acquired by varying resolutions to demonstrate the idea. A case study was designed to attain acceptable accuracy in gesture recognition under variant lighting. Using American Sign Language (ASL), the dataset was created and analyzed under various lighting conditions. In ASL-based images, significant feature points were selected using the scale-invariant feature transformation (SIFT). Finally, an artificial neural network (ANN) classified hand gestures using specified characteristics for validation. The suggested method was successful across a variety of illumination conditions and different image sizes. The total effectiveness of NN architecture was shown by the 97.6% recognition accuracy rate of 26 alphabets dataset with just a 2.4% error rate.

A Study on Iris Image Restoration Based on Focus Value of Iris Image (홍채 영상 초점 값에 기반한 홍채 영상 복원 연구)

  • Kang Byung-Jun;Park Kang-Ryoung
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.2 s.308
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    • pp.30-39
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    • 2006
  • Iris recognition is that identifies a user based on the unique iris texture patterns which has the functionalities of dilating or contracting pupil region. Iris recognition systems extract the iris pattern in iris image captured by iris recognition camera. Therefore performance of iris recognition is affected by the quality of iris image which includes iris pattern. If iris image is blurred, iris pattern is transformed. It causes FRR(False Rejection Error) to be increased. Optical defocusing is the main factor to make blurred iris images. In conventional iris recognition camera, they use two kinds of focusing methods such as lilted and auto-focusing method. In case of fixed focusing method, the users should repeatedly align their eyes in DOF(Depth of Field), while the iris recognition system acquires good focused is image. Therefore it can give much inconvenience to the users. In case of auto-focusing method, the iris recognition camera moves focus lens with auto-focusing algorithm for capturing the best focused image. However, that needs additional H/W equipment such as distance measuring sensor between users and camera lens, and motor to move focus lens. Therefore the size and cost of iris recognition camera are increased and this kind of camera cannot be used for small sized mobile device. To overcome those problems, we propose method to increase DOF by iris image restoration algorithm based on focus value of iris image. When we tested our proposed algorithm with BM-ET100 made by Panasonic, we could increase operation range from 48-53cm to 46-56cm.

Automatic Focusing Vision System for Inspection of Size and Shape of Small Hole (소형(1mm이하) hole의 형태 및 크기 측정을 위한 자동초점 비젼검사기)

  • Han, Moon-Yong;Han, Hern-Soo
    • Journal of the Korean Society for Precision Engineering
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    • v.16 no.10
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    • pp.80-86
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    • 1999
  • Since the quality of the coated wires is in various applications dependant on the coating depth, accuracy of hole size of dies used for coating wires must be maintained precisely, in general within one micron. This paper proposes a new vision system which measures automatically the size and shape of small holes having diameters less than 1mm within an error limit of 1 micron. To quickly obtain the focused image, this paper proposes an estimation method of the camera position using only a couple of defocused hole images. It measures the distributions of light intensity around the image boundary and decides the direction and distance of a camera motion. The proposed system measures the size, shape distortion, inclination of the hole against the axis of the dies structure, to decides the acceptability of the dies for use. The proposed algorithm has been implemented using a cheap 640${\times}$480 image system and has shown an average size error of 1micron when measuring the dieses having 0.1mm to 1.0mm diameters. It can be applied to the inspection of the size and position of holes in PCB, too.

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Entropy-Based 6 Degrees of Freedom Extraction for the W-band Synthetic Aperture Radar Image Reconstruction (W-band Synthetic Aperture Radar 영상 복원을 위한 엔트로피 기반의 6 Degrees of Freedom 추출)

  • Hyokbeen Lee;Duk-jin Kim;Junwoo Kim;Juyoung Song
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1245-1254
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    • 2023
  • Significant research has been conducted on the W-band synthetic aperture radar (SAR) system that utilizes the 77 GHz frequency modulation continuous wave (FMCW) radar. To reconstruct the high-resolution W-band SAR image, it is necessary to transform the point cloud acquired from the stereo cameras or the LiDAR in the direction of 6 degrees of freedom (DOF) and apply them to the SAR signal processing. However, there are difficulties in matching images due to the different geometric structures of images acquired from different sensors. In this study, we present the method to extract an optimized depth map by obtaining 6 DOF of the point cloud using a gradient descent method based on the entropy of the SAR image. An experiment was conducted to reconstruct a tree, which is a major road environment object, using the constructed W-band SAR system. The SAR image, reconstructed using the entropy-based gradient descent method, showed a decrease of 53.2828 in mean square error and an increase of 0.5529 in the structural similarity index, compared to SAR images reconstructed from radar coordinates.