• Title/Summary/Keyword: Edge estimation

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Comparative study of flexural stress estimation methods in concrete pavement considering tied concrete shoulder

  • Jeetendra S. Khichad;Rameshwar J. Vishwakarma;Samadhan G. Morkhade;Siddharth Mehndiratta
    • Structural Engineering and Mechanics
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    • v.90 no.2
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    • pp.177-187
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    • 2024
  • In this study, compared two distinct estimation methods (stress charts and regression equations) proposed by the Indian road congress design guideline (IRC:58-2015) to determine flexural stress in Jointed Plain Concrete Pavement (JPCP). The occurrence of critical flexural stresses in pavement slabs is due to the combined effects of wheel loads and temperature. These stresses depend on various factors such as material properties of concrete, soil-subgrade strength, loading, and geometric properties of the slab. In order to account for the practical variability of these factors, critical edge stresses are determined using both methods and compared considering tied concrete shoulder. IRC:58 (2015) suggests, the stresses calculated by both the procedures should provide the same results. However, when these stresses are compared for the same configurations and same loading conditions, large variations are observed. The effect of tied concrete shoulder on reduction in critical edge stress is observed. Based on the study, certain important conclusions and recommendations are presented.

A Spatial Error Concealment Technique with Low Complexity for Intra-frame in the H.264 Standard (H.264 인트라 프레임을 위한 저복잡도(低複雜度) 공간적 에러은닉 기법)

  • Kim Dong-Hyung;Cho Sang-Hyup;Jeong Je-Chang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.5C
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    • pp.503-511
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    • 2006
  • H.264 adopts new coding tools such as intra-prediction, loop filter, etc. The adoption of these tools enables an H.264-coded bitstream to have more information compared with previous standards. In this paper we proposed an effective spatial error concealment method for H.264. Among the information included in an H.264-coded bitstream, we use intra-mode for recovering a damaged block. This is because prediction direction in intra-mode is highly correlated to the edge direction of a lost macroblock. We first estimate the edge direction using intra-modes of blocks adjacent to a lost macroblock, and classify the area in a damaged macroblock into the edge and the flat area. And then our method recovers pixel values in the edge area using edge-directed interpolation, and recovers pixel values in the flat area using weighted interpolation. Simulation results show the proposed method yields better video quality than conventional approaches by 0.35 to 5.48 dB.

Estimation of Noise Level and Edge Preservation for Computed Tomography Images: Comparisons in Iterative Reconstruction

  • Kim, Sihwan;Ahn, Chulkyun;Jeong, Woo Kyoung;Kim, Jong Hyo;Chun, Minsoo
    • Progress in Medical Physics
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    • v.32 no.4
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    • pp.92-98
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    • 2021
  • Purpose: This study automatically discriminates homogeneous and structure edge regions on computed tomography (CT) images, and it evaluates the noise level and edge preservation ratio (EPR) according to the different types of iterative reconstruction (IR). Methods: The dataset consisted of CT scans of 10 patients reconstructed with filtered back projection (FBP), statistical IR (iDose4), and iterative model-based reconstruction (IMR). Using the 10th and 85th percentiles of the structure coherence feature, homogeneous and structure edge regions were localized. The noise level was estimated using the averages of the standard deviations for five regions of interests (ROIs), and the EPR was calculated as the ratio of standard deviations between homogeneous and structural edge regions on subtraction CT between the FBP and IR. Results: The noise levels were 20.86±1.77 Hounsfield unit (HU), 13.50±1.14 HU, and 7.70±0.46 HU for FBP, iDose4, and IMR, respectively, which indicates that iDose4 and IMR could achieve noise reductions of approximately 35.17% and 62.97%, respectively. The EPR had values of 1.14±0.48 and 1.22±0.51 for iDose4 and IMR, respectively. Conclusions: The iDose4 and IMR algorithms can effectively reduce noise levels while maintaining the anatomical structure. This study suggested automated evaluation measurements of noise levels and EPRs, which are important aspects in CT image quality with patients' cases of FBP, iDose4, and IMR. We expect that the inclusion of other important image quality indices with a greater number of patients' cases will enable the establishment of integrated platforms for monitoring both CT image quality and radiation dose.

Edge-Preserving Directional Regularization Technique for Disparity Estimation and Intermediate View Reconstruction of Stereoscopic Images (경계-보존 방향성 평활화를 이용한 양안 영상의 변이 추정과 중간 시점 영상의 재구성)

  • 김미현;강문기;이철희;최윤식;손광훈
    • Journal of Broadcast Engineering
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    • v.4 no.1
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    • pp.59-67
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    • 1999
  • In this paper, we study two important topics in stereoscopic image communication system. One is a disparity estimation (DE) method to obtain the depth information of a scene at the transmitter and the other is an intermediate view reconstruction(IVR) method at the receiver. We propose a new DE method using an edge-preserving directional regularization technique. The proposed DE method smooths disparity vectors in smooth regions and preserves edges without over-smoothing problem. It provides better reconstructed stereoscopic images and improved coding efficiency than the existing regularization techniques. In addition. we propose a new IVR method using interpolation and extrapolation techniques. The proposed IVR method preserves edge regions as well as occlusion regions well. Thus. it gives better intermediate views than the existing IVR methods.

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Reduction in Sample Size Using Topological Information for Monte Carlo Localization

  • Yang, Ju-Ho;Song, Jae-Bok;Chung, Woo-Jin
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.901-905
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    • 2005
  • Monte Carlo localization is known to be one of the most reliable methods for pose estimation of a mobile robot. Much research has been done to improve performance of MCL so far. Although MCL is capable of estimating the robot pose even for a completely unknown initial pose in the known environment, it takes considerable time to give an initial estimate because the number of random samples is usually very large especially for a large-scale environment. For practical implementation of the MCL, therefore, a reduction in sample size is desirable. This paper presents a novel approach to reducing the number of samples used in the particle filter for efficient implementation of MCL. To this end, the topological information generated off- line using a thinning method, which is commonly used in image processing, is employed. The topological map is first created from the given grid map for the environment. The robot scans the local environment using a laser rangefinder and generates a local topological map. The robot then navigates only on this local topological edge, which is likely to be the same as the one obtained off- line from the given grid map. Random samples are drawn near the off-line topological edge instead of being taken with uniform distribution, since the robot traverses along the edge. In this way, the sample size required for MCL can be drastically reduced, thus leading to reduced initial operation time. Experimental results using the proposed method show that the number of samples can be reduced considerably, and the time required for robot pose estimation can also be substantially decreased.

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JND based Illumination and Color Restoration Using Edge-preserving Filter (JND와 경계 보호 평탄화 필터를 이용한 휘도 및 색상 복원)

  • Han, Hee-Chul;Sohn, Kwan-Hoon
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.46 no.6
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    • pp.132-145
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    • 2009
  • We present the framework for JND based Illumination and Color Restoration Using Edge-preserving filter for restoring distorted images taken under the arbitrary lighting conditions. The proposed method is effective for appropriate illumination compensation, vivid color restoration, artifacts suppression, automatic parameter estimation, and low computation cost for HW implementation. We show the efficiency of the mean shift filter and sigma filter for illumination compensation with small spread parameter while considering the processing time and removing the artifacts such as HALO and noise amplification. The suggested CRF (color restoration filter) can restore the natural color and correct color distortion artifact more perceptually compared with current solutions. For the automatic processing, the image statistics analysis finds suitable parameter using JND and all constants are pre-defined. We also introduce the ROI-based parameter estimation dealing with small shadow area against spacious well-exposed background in an image for the touch-screen camera. The object evaluation is performed by CMC, CIEde2000, PSNR, SSIM, and 3D CIELAB gamut with state-of-the-art research and existing commercial solutions.

An Automatic Data Collection System for Human Pose using Edge Devices and Camera-Based Sensor Fusion (엣지 디바이스와 카메라 센서 퓨전을 활용한 사람 자세 데이터 자동 수집 시스템)

  • Young-Geun Kim;Seung-Hyeon Kim;Jung-Kon Kim;Won-Jung Kim
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.1
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    • pp.189-196
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    • 2024
  • Frequent false positives alarm from the Intelligent Selective Control System have raised significant concerns. These persistent issues have led to declines in operational efficiency and market credibility among agents. Developing a new model or replacing the existing one to mitigate false positives alarm entails substantial opportunity costs; hence, improving the quality of the training dataset is pragmatic. However, smaller organizations face challenges with inadequate capabilities in dataset collection and refinement. This paper proposes an automatic human pose data collection system centered around a human pose estimation model, utilizing camera-based sensor fusion techniques and edge devices. The system facilitates the direct collection and real-time processing of field data at the network periphery, distributing the computational load that typically centralizes. Additionally, by directly labeling field data, it aids in constructing new training datasets.

The Position Estimation of a Body Using 2-D Slit Light Vision Sensors (2-D 슬리트광 비젼 센서를 이용한 물체의 자세측정)

  • Kim, Jung-Kwan;Han, Myung-Chul
    • Journal of the Korean Society for Precision Engineering
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    • v.16 no.12
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    • pp.133-142
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    • 1999
  • We introduce the algorithms of 2-D and 3-D position estimation using 2-D vision sensors. The sensors used in this research issue red laser slit light to the body. So, it is very convenient to obtain the coordinates of corner point or edge in sensor coordinate. Since the measured points are normally not fixed in the body coordinate, the additional conditions, that corner lines or edges are straight and fixed in the body coordinate, are used to find out the position and orientation of the body. In the case of 2-D motional body, we can find the solution analytically. But in the case of 3-D motional body, linearization technique and least mean squares method are used because of hard nonlinearity.

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A Study on the Damage Estimation of CFRP using Acoustic Emission (음향방출을 이용한 탄소섬유강화 플라스틱의 손상 평가에 관한 연구)

  • 이장규;박성완;김봉각
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2003.10a
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    • pp.307-312
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    • 2003
  • The object of this study is to investigate a damage estimation of single edge cracked tensile specimens ($2_a$/W) as a function of acoustic emission (AE) according to the unidirectionally oriented carbon/epoxy composites, CFRP AE signals were analyzed and classified 3 regions by event counts, energy and amplitude for coressponding applied load. On tensile loading and using the results of the AE analysis, it was found that the event counts, cumulative counts or energy, and amplitude distributions useful for the prediction of damage failure.

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The Binarization of Text Regions in Natural Scene Images, based on Stroke Width Estimation (자연 영상에서 획 너비 추정 기반 텍스트 영역 이진화)

  • Zhang, Chengdong;Kim, Jung Hwan;Lee, Guee Sang
    • Smart Media Journal
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    • v.1 no.4
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    • pp.27-34
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    • 2012
  • In this paper, a novel text binarization is presented that can deal with some complex conditions, such as shadows, non-uniform illumination due to highlight or object projection, and messy backgrounds. To locate the target text region, a focus line is assumed to pass through a text region. Next, connected component analysis and stroke width estimation based on location information of the focus line is used to locate the bounding box of the text region, and each box of connected components. A series of classifications are applied to identify whether each CC(Connected component) is text or non-text. Also, a modified K-means clustering method based on an HCL color space is applied to reduce the color dimension. A text binarization procedure based on location of text component and seed color pixel is then used to generate the final result.

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