• Title/Summary/Keyword: 가중치 복원오차

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Sampling Set Selection Algorithm for Weighted Graph Signals (가중치를 갖는 그래프신호를 위한 샘플링 집합 선택 알고리즘)

  • Kim, Yoon Hak
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.1
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    • pp.153-160
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    • 2022
  • A greedy algorithm is proposed to select a subset of nodes of a graph for bandlimited graph signals in which each signal value is generated with its weight. Since graph signals are weighted, we seek to minimize the weighted reconstruction error which is formulated by using the QR factorization and derive an analytic result to find iteratively the node minimizing the weighted reconstruction error, leading to a simplified iterative selection process. Experiments show that the proposed method achieves a significant performance gain for graph signals with weights on various graphs as compared with the previous novel selection techniques.

SIFT Weighting Based Iterative Closest Points Method in 3D Object Reconstruction (3차원 객체 복원을 위한 SIFT 특징점 가중치 기반 반복적 점군 정합 방법)

  • Shin, Dong-Won;Ho, Yo-Sung
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2016.06a
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    • pp.309-312
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    • 2016
  • 최근 실세계에 존재하는 물체의 3차원 형상과 색상을 디지털화하는 3차원 객체 복원에 대한 관심이 날로 증가하고 있다. 3차원 객체 복원은 영상 획득, 영상 보정, 점군 획득, 반복적 점군 정합, 무리 조정, 3차원 모델 표현과 같은 단계를 거처 통합된 3차원 모델을 생성한다. 그 중 반복적 점군 정합 방법은 카메라 궤적의 초기 값을 획득하는 방법으로서 무리 조정 단계에서 전역 최적 값으로의 수렴을 보장하기 위해 중요한 단계이다. 기존의 반복적 점군 정합 (iterative closest points) 방법에서는 시간이 지남에 따라 누적된 궤적 오차 때문에 발생하는 객체 표류 문제가 발생한다. 본 논문에서는 이 문제를 해결하기 위해 색상 영상에서 SIFT 특징점을 획득하고 3차원 점군을 얻은 뒤 가중치를 부여함으로써 점 군 간의 더 정확한 정합을 수행한다. 실험결과에서 기존의 방법과 비교하여 제안하는 방법이 절대 궤적 오차 (absolute trajectory error)가 감소하는 것을 확인 했고 복원된 3차원 모델에서 객체 표류 현상이 줄어드는 것을 확인했다.

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An Image Inpainting Method using Global Information and Distance Weighting (전역적 특성과 거리가중치를 이용한 영상 인페인팅)

  • Kim, Chang-Ki;Kim, Baek-Sop
    • Journal of KIISE:Software and Applications
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    • v.37 no.8
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    • pp.629-640
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    • 2010
  • The exemplar-based inpainting model is widely used to remove objects from natural images and to restore a damaged region. This paper presents a method which improves the performance of the conventional exemplar-based inpainting model by modifying three major parts in the model: data term, confidence term and patch selection. While the conventional data term is calculated using the local gradient, the proposed method uses 16 compass masks to get the global gradient to make the method robust to noise. To overcome the problem that the confidence term gets negligible in the inside of the eliminated region, a method is proposed which makes the confidence term decrease slowly in the eliminated region. The patch selection procedure is modified so that the closer patch has higher weight. Experiments showed that the proposed method produced more natural images and lower reconstruction error than the conventional exemplar-based inpainting.

Color Restoration Method Using the Dichromatic Reflection Model for Low-light-level Environments (저조도 환경에 적합한 이색도 반사 모델을 이용한 색 복원 기법)

  • Lee, Woo-Ram;Jun, WooKyoung;Jun, Byoung-Min
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.12
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    • pp.7324-7330
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    • 2014
  • Color distortion of the dark images acquired under a low-light-level environment with a weak light source can be cause of the performance decreation of various vision systems. Therefore, recovering the original color of the images is an important process for enhancing the performance of the system. For this, this study proposes a color restoration method using a dichromatic reflection model. This paper assumes that the dark images can be classified into two parts affected by specular or diffuse reflection. Two different color constancy methods were then applied to the images to remove the effects of each reflection and two images were created as a result. The resulting images produced a one color-corrected image by combining with different weights according to the position in the images. For the performance evaluation, this paper used a synthesized image, and considered the Euclidean distance and angular error as an evaluation factor. In addition, a performance comparison was performed with the existing various color constancy method to achieve the objectivity of evaluation. The experimental results showed that the proposed method can be a more suitable solution for color restoration than the existing method.

On Shape Recovery of 3D Object from Multiple Range Images (시점이 다른 다수의 거리 영상으로부터 3차원 물체의 형상 복원)

  • Kim, Jun-Young;Yun, Il-Dong;Lee, Sang-Uk
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.37 no.1
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    • pp.1-15
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    • 2000
  • To reconstruct 3- D shape, It is a common strategy to acquire multiple range Images from different viewpoints and integrate them into a common coordinates In this paper, we particularly focus on the registration and integration processes for combining all range Images into one surface model. For the registration, we propose the 2-step registration algorithm, which consists of 2 steps the rough registration step using all data points and the fine registration step using the high-curved data points For the integration, we propose a new algorithm, referred to as ‘multi-registration’ technique, to alleviate the error accumulation problem, which occurs during applying the pair-wise registration to each range image sequentially, in order to transform them into a common reference frame Intensive experiments are performed on the various real range data In experiments, all range images were registered within 1 minutes on Pentium 150MHz PC The results show that the proposed algorithms registrate and integrate multiple range Images within a tolerable error bound in a reasonable computation time, and the total error between all range Images are equalized with our proposed algorithms.

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Development of Tomographic Scan Method for Industrial Plants (산업공정반응기의 감마선 전산 단층촬영기술 개발)

  • Kim, Jong-Bum;Jung, Sung-Hee;Moon, Jin-Ho;Kwon, Taek-Yong;Cho, Gyu-Seong
    • Journal of the Korean Society for Nondestructive Testing
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    • v.30 no.1
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    • pp.20-30
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    • 2010
  • In this paper, a new tomographic scan method with fixed installed detectors and rotating source from gamma projector was presented to diagnose the industrial plants which were impossible to be examined by conventional tomographic systems. Weight matrix calculation method which was suitable for volumetric detector and statistical iterative reconstruction method were applied for reconstructing the simulation and experimental data. Monte Carlo simulations had been performed for two kinds of phantoms. Lab scale experiment with a same condition as one of phantoms, had been carried out. Simulation results showed that reconstruction from photopeak counting measurement gave the better results than from the gross counting measurement although photopeak counting measurement had large statistical errors. Experimental data showed the similar result as Monte Carlo simulation. Those results appeared to be promising for industrial tomographic applications, especially for petrochemical industries.