• Journal of Digital Contents Society
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• v.16 no.1
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• pp.25-32
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• 2015

With the increased frequency of crime such as assaults and sexual violence, the reliance on CCTV in arresting criminals has increased as well. However, CCTV, which should be monitored by human labor force at all times, has limits in terms of budget and man-power. Thereby, the interest in intelligent security system is growing nowadays. Expanding the techniques of an objects behavior recognition in previous studies, we propose a system to detect forms of violence between 2~3 objects from images obtained in CCTV. It perceives by detecting the object with the difference operation and the morphology of the background image. The determinant criteria to define violent behaviors are suggested. Moreover, provable decision metric values through measurements of the number of violent condition are derived. As a result of the experiments with the threshold values, showed more than 80% recognition success rate. A future research for abnormal behaviors recognition system in a crowded circumstance remains to be developed.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.165-171
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• 2018

Shadow is a physical phenomenon observed in natural scenes and has a negative effect on various image processing systems such as intelligent video surveillance, traffic surveillance and aerial imagery analysis. Therefore, shadow detection should be considered as a preprocessing process in all areas of computer vision. In this paper, we define and analyze various feature elements for shadow detection in a single natural image that does not require a reference image. The shadow elements describe the intensity, chromaticity, illuminant-invariant, color invariance, and entropy image, which indicate the uncertainty of the information. The results show that the chromaticity and illuminant-invariant images are effective for shadow detection. In the future, we will define a fusion map of various shadow feature elements, and continue to study shadow detection that can adapt to various lighting levels, and shadow removal using chromaticity and illuminance invariant images.

• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.11-17
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• 2016

In this paper, we proposed a multi-viewer system with multiple HD cameras based AVB(Audio Video Bridge) ethernet cable using IP networking, and FPGA(Xilinx Zynq 702) for bus safety systems. This AVB (IEEE802.1BA) system can be designed for the low latency based on FPGA, and transmit real-time with HD video and audio signals in a vehicle network. The proposed multi-viewer platform can multiplex H.264 video signals from 4 wide-angle HD cameras with existed ethernet 1Gbps. and 2-wire 100Mbps cables. The design of Zynq 702 based low latency to H.264 AVC CODEC was proposed for the minimization of time-delay in the HD video transmission of car area network, too. And the performance of PSNR(Peak Signal-to-noise-ratio) was analyzed with the reference model JM for encoding and decoding results in H.264 AVC CODEC. These PSNR values can be confirmed according the theoretical and HW result from the signal of H.264 AVC CODEC based on Zynq 702 the multi-viewer with multiple cameras. As a result, proposed AVB multi-viewer platform with multiple cameras can be used for the surveillance of audio and video around a bus for the safety due to the low latency of H.264 AVC CODEC design.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1268-1280
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• 2015

In video surveillance system, the exposure of a person's face is a serious threat to personal privacy. To protect the personal privacy in large amount of videos, an automatic face detection method is required to locate and mask the person's face. However, in real-world surveillance videos, the effectiveness of existing face detection methods could deteriorate due to large variations in facial appearance (e.g., facial pose, illumination etc.) or degraded face (e.g., occluded face, low-resolution face etc.). This paper proposes a new face detection method based on multi-level facial features. In a video frame, different kinds of spatial features are independently extracted, and analyzed, which could complement each other in the aforementioned challenges. Temporal domain analysis is also exploited to consolidate the proposed method. Experimental results show that, compared to competing methods, the proposed method is able to achieve very high recall rates while maintaining acceptable precision rates.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.450-453
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• 2011

고화질의 디지털 카메라 및 스마트폰, 감시용 카메라의 보급 등으로 인해 최근 패턴 인식 및 이미지 프로세싱 분야에서 고화질의 이미지 및 비디오를 처리해야 하는 경우가 많아지고 있다. 특히 차량 번호판 감지 등과 같은 객체 인식 분야의 경우, 고화질의 이미지로 인해 그만큼 인식에 필요한 계산 비용이 증가하게 되었는데 따라서 이러한 계산 비용을 효율적으로 줄이기 위한 기법이 요구되고 있다. 또한 기존의 차량 번호판 감지의 도메인과는 다르게 도로 상에서의 실시간 차량 번호판 감지의 필요성이 대두되고 있기에 본 논문에서는 도로 상에서의 실시간 번호판 감지 시스템을 위한 차량 번호판 주변정보 기반의 효율적인 윈도우 슬라이딩(window sliding) 방법을 제안한다. 본 논문의 시스템은 총 3단계로, (1) SVM(Supported Vector Machine) 을 통한 차량 번호판 주위 정보에 대한 학습, (2) 도로 상의 번호판 위치 확률 모델링을 통한 탐색 공간의 감소, (3) $context_{plate}$분류기를 통한 OCS(operator context scanning)의 수행이다. 이와 같은 $context_{plate}$분류기와 OCS를 통해 번호판 검출을 위한 윈도우 슬라이딩의 수가 크게 줄었음을 알 수 있었으며, 또한 번호판의 정보를 건너뛰지 않고, 신뢰성 있게 접근함을 알 수 있었다.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.484-486
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• 2005

Passenger safety is a primary concern of railway system but, it has been urgent issue that dozens of people are killed every year when they falloff from train platforms. Recently, advancements in IT have enabled applying vision sensors to railway environments, such as CCTV and stereo camera sensors. In this paper, we propose a stereoscopic video coding scheme for subway accident monitoring system. The proposed scheme is designed for providing flexible video among various displays, such as control center, station employees and train driver. We uses MPEG-2 standard for coding the left-view sequence and IBMDC for predicting the P- and B-types of frames of the right-view sequence. IBMDC predicts matching block by interpolating both motion and disparity predicted macroblocks. To provide efficient stereoscopic video service. we define both temporally and spatially scalable layers for each eye's-view by using the concept of Spatio-Temporal scalability. According to the experimental results. we expect the proposed functionalities will play a key role in establishing highly flexible stereoscopic video codec for ubiquitous display environment where devices and network connections are heterogeneous.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.580-584
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• 2005

One of the problems of panoramic image stitching methods is that its computational cost is so high that the image processing required usually cannot be done in real-time. Real-time performance is important in applications such as video surveillance becausewe must see current scenes. But it takes more than several seconds to calculate transform coefficients between images. Panoramic VR technologies such as Apple QuickTime VR have problem that distorts images of top and bottom. This paper presents a fast stitching method and a methpd reducing distortions of top and bottom in cubic panoramic image.

• Journal of Advanced Navigation Technology
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• v.18 no.4
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• pp.387-392
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• 2014

Recently, various research for intelligent video surveillance system have been proposed, but the existing monitoring systems are inefficient because all of situational awareness is judged by the human. In this paper, shadow removal based moving object tracking method is proposed using the chromaticity and entropy image. The background subtraction model, effective in the context awareness environment, has been applied for moving object detection. After detecting the region of moving object, the shadow candidate region has been estimated and removed by RGB based chromaticity and minimum cross entropy images. For the validity of the proposed method, the highway video is used to experiment. Some experiments are conducted so as to verify the proposed method, and as a result, shadow removal and moving object tracking are well performed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.236-238
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• 2003

Human face detection is often the first step in applications such as video surveillance, human computer interface, fare recognition, and image database management. We have constructed a simple and fast system to detect frontal human faces in complex environment and different illumination. This paper presents a fast segmentation method to combine neighboring pixels with similar hue. The algorithm constructs eye, mouth, and boundary maps for verifying each fare candidate. We test the system on images in complex environment and with confusing objects. The experiment shows a robust detection result with few false detected fates.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.298-301
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• 2012

This paper presents a graph-based method of detecting and tracking moving objects in H.264/SVC bitstreams for video surveillance applications that makes use the information from spatial base and enhancement layers of the bitstreams. In the base layer, segmentation of real moving objects are first performed using a spatio-temporal graph by removing false detected objects via graph pruning and graph projection, followed by graph matching to precisely identify the real moving objects over time even under occlusion. For the accurate detection and reliable tracking of moving objects in the enhancement layer, as well as saving computational complexity, the identified block groups of the real moving objects in the base layer are then mapped to the enhancement layer to provide accurate and efficient object detection and tracking in the bitstreams of higher resolution. Experimental results show the proposed method can produce reliable results with low computational complexity in both spatial layers of H.264/SVC test bitstreams.