• Title/Summary/Keyword: 참조 배경

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Robust Method of Updating Reference Background Image in Unstable Illumination Condition (불안정한 조명 환경에 강인한 참조 배경 영상의 갱신 기법)

  • Ji, Young-Suk;Han, Young-Joon;Hahn, Hern-Soo
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.1
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    • pp.91-102
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    • 2010
  • It is very difficult that a previous surveillance system and vehicle detection system find objects on a limited and unstable illumination condition. This paper proposes a robust method of adaptively updating a reference background image for solving problems that are generated by the unstable illumination. The first input image is set up as the reference background image, and is divided into three block categories according to an edge component. Then a block state analysis, which uses a rate of change of the brightness, a stability, a color information, and an edge component on each block, is applied to the input image. On the reference background image, neighbourhood blocks having the same state of a updated block are merged as a block. The proposed method can generate a robust reference background image because it distinguishes a moving object area from an unstable illumination. The proposed method very efficiently updates the reference background image from the point of view of the management and the processing time. In order to demonstrate the superiority of the proposed stable manner in situation that an illumination quickly changes.

A Study of Reference Image Generation for Moving Object Detection under Moving Camera (이동카메라에서 이동물체 검출을 위한 참조 영상 생성에 관한 연구)

  • Lee, June-Hyung;Chae, Ok-Sam
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.3
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    • pp.67-73
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    • 2007
  • This paper presents a panoramic reference image generation based automatic algorithm for moving objects detection robust to illumination variations under moving camera. Background image is generated by rotating the fixed the camera on the tripod horizontally. aligning and reorganizing this images. In generation of the cylindrical panoramic image, most of previous works assume the static environment. We propose the method to generating the panoramic reference image from dynamic environments in this paper. We develop an efficient approach for panoramic reference image generation by using accumulated edge map as well as method of edge matching between input image and background image. We applied the proposed algorithm to real image sequences. The experimental results show that panoramic reference image generation robust to illumination variations can be possible using the proposed method.

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Background Noise Reduction Algorithm Based on Frequency Domain Adaptive Filter and MMSE-LSA in Dual-microphone situation (Dual-microphone 환경에서 주파수 영역 적응 필터와 MMSE-LSA기반 배경 잡음 알고리즘)

  • Lee, Keunsang;Park, Youngchul
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.6 no.1
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    • pp.23-28
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    • 2013
  • In this paper, background noise reduction method using dual microphone is proposed in mobile environment. Each Signal, reference and primary, would be replaced by microphone input signals, which were measured by reference and primary microphones, and then, noise reduction was performed using FDAF. After then, residual and background noise would be estimated and reduced by MMSE-LSA. For consistent noise reduction performance, result of VAD that could be caculated by PLD between two microphones was used.

Reference Implementation of OpenVG for Embedded System (임베디드 시스템용 OpenVG 참조 구현)

  • Lee, Sang-Yun;Lee, Kyung-Hee;Kim, Sung-Hwan;Chung, Ji-Hoon;Choi, Byung-Uk
    • Proceedings of the Korean Information Science Society Conference
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    • 2007.06b
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    • pp.161-166
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    • 2007
  • 본 논문에서는 크로노스 그룹에서 제정한 스케일러블 벡터 그래픽 하드웨어 가속을 위한 표준인 OpenVG를 소프트웨어 렌더링 방식으로 구현한 참조 구현을 제안한다. EGL과 OpenVG 엔진이 다양한 임베디드 환경에 쉽게 이식이 가능하도록 설계한 방식을 제시한다 또한 성능 개선을 위해, 채택한 수학 함수와 알고리즘의 선택 배경을 기술하고 최적의 렌더링 방법을 제안한다. 소프트웨어 렌더링 방법으로 구현한 OpenVG를 통해 벡터 이미지를 화면에 출력하는 모습을 보인다. 또한 호환성 테스트 툴인 CTS의 테스트 결과를 제시하며 기존 참조 구현인 Hybrid 사의 참조 구현과 성능 비교 실험 결과를 보인다.

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Automatic Pedestrian Removal Algorithm Using Multiple Frames (다중 프레임에서의 보행자 검출 및 삭제 알고리즘)

  • Kim, ChangSeong;Lee, DongSuk;Park, Dong Sun
    • Smart Media Journal
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    • v.4 no.2
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    • pp.26-33
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    • 2015
  • In this paper, we propose an efficient automatic pedestrian removal system from a frame in a video sequence. It firstly finds pedestrians from the frame using a Histogram of Oriented Gradient(HOG) / Linear-Support Vector Machine(L-SVM) classifier, searches for proper background patches, and then the patches are used to replace the deleted pedestrians. Background patches are retrieved from the reference video sequence and a modified feather blender algorithm is applied to make boundaries of replaced blocks look naturally. The proposed system, is designed to automatically detect object and generate natural-looking patches, while most existing systems provide search operation in manual. In the experiment, the average PSNR of the replaced blocks is 19.246

Automatic Attention Object Extraction Using Feature Maps (특징 지도를 이용한 자동적인 중심 객체 추출)

  • Park Ki-Tae;Kim Jong-Hyeok;Moon Young-Shik
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.06b
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    • pp.370-372
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    • 2006
  • 본 논문에서 제안하는 방법은 영상에서 중심 객체를 추출하기 위해 에지와 색상 정보에서 추출한 특집 지도와 배경의 영향을 줄이기 위친 창조 지도(reference map)를 제안한 것이 특징이다. 특징 지도는 다른 영역과 현저하게 구분되는 영역을 검출하기 위해서 영상의 특징 값(feature)들을 이용해서 구성한 영상이라고 할 수 있다. 그리고 창조 지도는 배경의 영향을 최소화하면서, 객체가 존재할 확률이 높은 부분을 나타내는 지도이다. 제안하는 방법은 밝기 차 정보를 가지고 있는 에지와 YCbCr 컬러모델과 HSV 컬러모델의 색상 성분을 특징 값으로 사용한다. 이들 특징 값을 이용해서 특징 지도를 구성하는 방법으로 영상 내 색상 차에 의해서 나타나는 경계부분을 구하는 방법을 사용한다. 이 방법을 사용하여 에지 지도와 두 개의 색상 지도의 3가지 특징 지도를 생성한다. 다음으로, 영상 배경의 영향을 줄이기 위해 참조 지도를 구한다. 구해진 참조 지도와 특징 지도들을 이용해서 결합 지도(combination map)를 생성한다. 결함 지도로부터 다각형의 객체 후보 영역을 구하고, 객체 후보 영역에 영상분할을 적용하여 중심 객체를 추출한다. 실험에 사용된 영상들은 Corel DB를 사용하였으며, 실험결과로써 precision은 84.3%, recall은 81.3%의 성능을 보인다.

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Motion Estimation Method by Using Depth Camera (깊이 카메라를 이용한 움직임 추정 방법)

  • Kwon, Soon-Kak;Kim, Seong-Woo
    • Journal of Broadcast Engineering
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    • v.17 no.4
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    • pp.676-683
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    • 2012
  • Motion estimation in video coding greatly affects implementation complexity. In this paper, a reducing method of the complexity in motion estimation is proposed by using both the depth and color cameras. We obtain object information with video sequence from distance information calculated by depth camera, then perform labeling for grouping pixels within similar distances as the same object. Three search regions (background, inside-object, boundary) are determined adaptively for each of motion estimation blocks within current and reference pictures. If a current block is the inside-object region, then motion is searched within the inside-object region of reference picture. Also if a current block is the background region, then motion is searched within the background region of reference picture. From simulation results, we can see that the proposed method compared to the full search method remains the almost same as the motion estimated difference signal and significantly reduces the searching complexity.

Extraction of Attentive Objects Using Feature Maps (특징 지도를 이용한 중요 객체 추출)

  • Park Ki-Tae;Kim Jong-Hyeok;Moon Young-Shik
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.5 s.311
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    • pp.12-21
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    • 2006
  • In this paper, we propose a technique for extracting attentive objects in images using feature maps, regardless of the complexity of images and the position of objects. The proposed method uses feature maps with edge and color information in order to extract attentive objects. We also propose a reference map which is created by integrating feature maps. In order to create a reference map, feature maps which represent visually attentive regions in images are constructed. Three feature maps including edge map, CbCr map and H map are utilized. These maps contain the information about boundary regions by the difference of intensity or colors. Then the combination map which represents the meaningful boundary is created by integrating the reference map and feature maps. Since the combination map simply represents the boundary of objects we extract the candidate object regions including meaningful boundaries from the combination map. In order to extract candidate object regions, we use the convex hull algorithm. By applying a segmentation algorithm to the area of candidate regions to separate object regions and background regions, real object regions are extracted from the candidate object regions. Experiment results show that the proposed method extracts the attentive regions and attentive objects efficiently, with 84.3% Precision rate and 81.3% recall rate.

Video Segmentation Using Image signal and Human characteristic (영상신호 특성 및 Human 특징을 이용한 실시간 영상 분류)

  • Kim, Min-Joon;Kim, Won-Ha
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2016.06a
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    • pp.284-287
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    • 2016
  • 영상에서 배경으로부터 객체를 분류하는 영상 분류 알고리즘은 물체 인식 및 추적 등 다양한 응용분야에서 중요하다. 본 논문에서는 고정된 카메라에서 다수의 초기 프레임을 참조하여 실시간 영상 분류 방법을 제안한다. 먼저 전경과 배경을 구분하는 확률모델을 제안하였으며 초기 프레임 동안에 카메라의 특성을 추출하여 카메라에 적응적으로 영상을 분류한다. 또한 분류된 영상에서 human의 특징을 이용하여 분류된 결과를 보정하는 방법을 제안한다. 마지막으로 제안한 알고리즘의 실시간 분류 처리를 위하여 복잡도를 최소화 하였다.

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Depth-map Preprocessing Algorithm Using Two Step Boundary Detection for Boundary Noise Removal (경계 잡음 제거를 위한 2단계 경계 탐색 기반의 깊이지도 전처리 알고리즘)

  • Pak, Young-Gil;Kim, Jun-Ho;Lee, Si-Woong
    • The Journal of the Korea Contents Association
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    • v.14 no.12
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    • pp.555-564
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    • 2014
  • The boundary noise in image syntheses using DIBR consists of noisy pixels that are separated from foreground objects into background region. It is generated mainly by edge misalignment between the reference image and depth map or blurred edge in the reference image. Since hole areas are generally filled with neighboring pixels, boundary noise adjacent to the hole is the main cause of quality degradation in synthesized images. To solve this problem, a new boundary noise removal algorithm using a preprocessing of the depth map is proposed in this paper. The most common way to eliminate boundary noise caused by boundary misalignment is to modify depth map so that the boundary of the depth map can be matched to that of the reference image. Most conventional methods, however, show poor performances of boundary detection especially in blurred edge, because they are based on a simple boundary search algorithm which exploits signal gradient. In the proposed method, a two-step hierarchical approach for boundary detection is adopted which enables effective boundary detection between the transition and background regions. Experimental results show that the proposed method outperforms conventional ones subjectively and objectively.