• Title/Summary/Keyword: shadow detection

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Crack Detection on Concrete Bridge by Image Processing Technique (영상처리 기법을 이용한 콘크리트 교량의 균열 검출)

  • Kim, Hyung-Jin;Lee, Jeong-Ho;Moon, Young-Shik
    • Proceedings of the IEEK Conference
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    • 2007.07a
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    • pp.381-382
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    • 2007
  • In this paper, crack detection technique of concrete bridge is proposed robust against shadow and noise. Our technique consists of two steps. In the first step, crack candidate region is detected by preprocessing. Preprocessing techniques such as median filter, isolated point filter and morphological techniques, use utilized for detection of crack candidate regions. In the final step, crack is detected from crack candidate region by considering any connectivity between cracks. By experimental results, performance is improved 6.8% over the existing method.

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An Approach to Video Based Traffic Parameter Extraction (영상을 기반 교통 파라미터 추출에 관한 연구)

  • Yu, Mei;Kim, Yong-Deak
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.38 no.5
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    • pp.42-51
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    • 2001
  • Vehicle detection is the basic of traffic monitoring. Video based systems have several apparent advantages compared with other kinds of systems. However, In video based systems, shadows make troubles for vehicle detection, especially active shadows resulted from moving vehicles. In this paper, a new method that combines background subtraction and edge detection is proposed for vehicle detection and shadow rejection. The method is effective and the correct rate of vehicle detection is higher than 98% in experiments, during which the passive shadows resulted from roadside buildings grew considerably. Based on the proposed vehicle detection method, vehicle tracking, counting, classification and speed estimation are achieved so that traffic parameters concerning traffic flow is obtained to describe the load of each lane.

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A Study On the Image Based Traffic Information Extraction Algorithm (영상기반 교통정보 추출 알고리즘에 관한 연구)

  • 하동문;이종민;김용득
    • Journal of Korean Society of Transportation
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    • v.19 no.6
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    • pp.161-170
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    • 2001
  • Vehicle detection is the basic of traffic monitoring. Video based systems have several apparent advantages compared with other kinds of systems. However, In video based systems, shadows make troubles for vehicle detection. especially active shadows resulted from moving vehicles. In this paper a new method that combines background subtraction and edge detection is proposed for vehicle detection and shadow rejection. The method is effective and the correct rate of vehicle detection is higher than 98(%) in experiments, during which the passive shadows resulted from roadside buildings grew considerably. Based on the proposed vehicle detection method, vehicle tracking, counting, classification and speed estimation are achieved so that traffic information concerning traffic flow is obtained to describe the load of each lane.

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Moving Object Detection Using Sparse Approximation and Sparse Coding Migration

  • Li, Shufang;Hu, Zhengping;Zhao, Mengyao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.5
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    • pp.2141-2155
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    • 2020
  • In order to meet the requirements of background change, illumination variation, moving shadow interference and high accuracy in object detection of moving camera, and strive for real-time and high efficiency, this paper presents an object detection algorithm based on sparse approximation recursion and sparse coding migration in subspace. First, low-rank sparse decomposition is used to reduce the dimension of the data. Combining with dictionary sparse representation, the computational model is established by the recursive formula of sparse approximation with the video sequences taken as subspace sets. And the moving object is calculated by the background difference method, which effectively reduces the computational complexity and running time. According to the idea of sparse coding migration, the above operations are carried out in the down-sampling space to further reduce the requirements of computational complexity and memory storage, and this will be adapt to multi-scale target objects and overcome the impact of large anomaly areas. Finally, experiments are carried out on VDAO datasets containing 59 sets of videos. The experimental results show that the algorithm can detect moving object effectively in the moving camera with uniform speed, not only in terms of low computational complexity but also in terms of low storage requirements, so that our proposed algorithm is suitable for detection systems with high real-time requirements.

Detection of Pulmonary Nodules' Shadow on Chest X-ray Image (흉부 X선 영상에서 폐 종류 음영 검출)

  • Kim, Eung-Kyeu
    • Proceedings of the KIEE Conference
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    • 2007.07a
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    • pp.327-328
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    • 2007
  • 에너지 흉부 단순 X선 영상으로부터 폐 종류 음영을 검출하기 위한 필터를 예측해서 성능좋게 평가하기 위한 방법을 제안한다. 더욱이 그 평가방법을 이용해서 기존에 제안된 다중 해상도 2G 필터의 평가를 행한다. 전문의의 진단보조 혹은 총합자동진단시스템의 구성요소로서 필터가 수행한 역할을 고려한 후, 필터가 만족해야만 하는 조건 및 그 조건을 만족한 경우에 있어서 몇가지 성능평가 척도를 명확히 한다. 제안한 평가방법을 통해서 다중해상도 필터가 단일해상도 필터에 비해 좋은 성능을 나타내고 있음을 명확히 한다.

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An Authentication Protocol-based Multi-Layer Clustering for Mobile Ad Hoc Networks (이동 Ad Hoc 망을 위한 다중 계층 클러스터링 기반의 인증 프로토콜)

  • Lee Keun-Ho;Han Sang-Bum;Suh Heyi-Sook;Lee Sang-Keun;Hwang Chong-Sun
    • Journal of KIISE:Information Networking
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    • v.33 no.4
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    • pp.310-323
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    • 2006
  • In this paper, we describe a secure cluster-routing protocol based on a multi-layer scheme in ad hoc networks. We propose efficient protocols, Authentication based on Multi-layer Clustering for Ad hoc Networks (AMCAN), for detailed security threats against ad hoc routing protocols using the selection of the cluster head (CH) and control cluster head (CCH) using a modification of cluster-based routing ARCH and DMAC. This protocol provides scalability of Shadow Key using threshold authentication scheme in ad hoc networks. The proposed protocol comprises an end-to-end authentication protocol that relies on mutual trust between nodes in other clusters. This scheme takes advantage of Shadow Key using threshold authentication key configuration in large ad hoc networks. In experiments, we show security threats against multilayer routing scheme, thereby successfully including, establishment of secure channels, the detection of reply attacks, mutual end-to-end authentication, prevention of node identity fabrication, and the secure distribution of provisional session keys using threshold key configuration.

Robust Traffic Monitoring System by Spatio-Temporal Image Analysis (시공간 영상 분석에 의한 강건한 교통 모니터링 시스템)

  • 이대호;박영태
    • Journal of KIISE:Software and Applications
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    • v.31 no.11
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    • pp.1534-1542
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    • 2004
  • A novel vision-based scheme of extracting real-time traffic information parameters is presented. The method is based on a region classification followed by a spatio-temporal image analysis. The detection region images for each traffic lane are classified into one of the three categories: the road, the vehicle, and the shadow, using statistical and structural features. Misclassification in a frame is corrected by using temporally correlated features of vehicles in the spatio-temporal image. Since only local images of detection regions are processed, the real-time operation of more than 30 frames per second is realized without using dedicated parallel processors, while ensuring detection performance robust to the variation of weather conditions, shadows, and traffic load.

Adaptive Cooperative Spectrum Sensing Based on SNR Estimation in Cognitive Radio Networks

  • Ni, Shuiping;Chang, Huigang;Xu, Yuping
    • Journal of Information Processing Systems
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    • v.15 no.3
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    • pp.604-615
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    • 2019
  • Single-user spectrum sensing is susceptible to multipath effects, shadow effects, hidden terminals and other unfavorable factors, leading to misjudgment of perceived results. In order to increase the detection accuracy and reduce spectrum sensing cost, we propose an adaptive cooperative sensing strategy based on an estimated signal-to-noise ratio (SNR). Which can adaptive select different sensing strategy during the local sensing phase. When the estimated SNR is higher than the selection threshold, adaptive double threshold energy detector (ED) is implemented, otherwise cyclostationary feature detector is performed. Due to the fact that only a better sensing strategy is implemented in a period, the detection accuracy is improved under the condition of low SNR with low complexity. The local sensing node transmits the perceived results through the control channel to the fusion center (FC), and uses voting rule to make the hard decision. Thus the transmission bandwidth is effectively saved. Simulation results show that the proposed scheme can effectively improve the system detection probability, shorten the average sensing time, and has better robustness without largely increasing the costs of sensing system.

Tracking and Face Recognition of Multiple People Based on GMM, LKT and PCA

  • Lee, Won-Oh;Park, Young-Ho;Lee, Eui-Chul;Lee, Hee-Kyung;Park, Kang-Ryoung
    • Journal of Korea Multimedia Society
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    • v.15 no.4
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    • pp.449-471
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    • 2012
  • In intelligent surveillance systems, it is required to robustly track multiple people. Most of the previous studies adopted a Gaussian mixture model (GMM) for discriminating the object from the background. However, it has a weakness that its performance is affected by illumination variations and shadow regions can be merged with the object. And when two foreground objects overlap, the GMM method cannot correctly discriminate the occluded regions. To overcome these problems, we propose a new method of tracking and identifying multiple people. The proposed research is novel in the following three ways compared to previous research: First, the illuminative variations and shadow regions are reduced by an illumination normalization based on the median and inverse filtering of the L*a*b* image. Second, the multiple occluded and overlapped people are tracked by combining the GMM in the still image and the Lucas-Kanade-Tomasi (LKT) method in successive images. Third, with the proposed human tracking and the existing face detection & recognition methods, the tracked multiple people are successfully identified. The experimental results show that the proposed method could track and recognize multiple people with accuracy.

Hue-based Noise-tolerant Corner Detector Robust to Shadows (그림자에 강건한 색상 기반 내잡음성 코너 검출자)

  • 박기현;박은진;최흥문
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.6
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    • pp.239-245
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    • 2004
  • A hue-based noise-tolerant corner detector is proposed for the exact detection of the real corners in spite of the shadows and random noise. Based on the fact that the hue gradient at the border of the opaque objects' shadow is smaller than the intensity gradient in HSI (hue-saturation-intensity) color space, the effects of shadow are eliminated by introducing the hue-weighted combination of vector gradient to the proposed corner detector. Furthermore, the proposed corner detector is robust to random noise by offsetting the contribution to the corner candidate when the polarities of the color gradients of the pixel pairs are out of phase each other. Results of the experiment show that the proposed corner detector can effectively detect the real corners.