• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.11
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• pp.1069-1076
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• 2016

Recent development in visual sensor technologies has encouraged various researches on adding imaging capabilities to sensor networks. Video data are bigger than other sensor data, so it is essential to manage the amount of image data efficiently. In this paper, a new method of video traffic estimation is proposed for efficient traffic management of visual sensor networks. In the proposed method, a first order autoregressive model is used for modeling the traffic with the consideration of the characteristics of video traffics acquired from visual sensors, and a Kalman filter algorithm is used to estimate the amount of video traffics. The proposed method is computationally simple, so it is proper to be applied to sensor nodes. It is shown by experimental results that the proposed method is simple but estimate the video traffics exactly by less than 1% of the average.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.707-714
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• 2019

Recently, as the sensor network technologies and camera technologies develops, there are increasing needs by combining two technologies to effectively observe or monitor the areas that are difficult for people to access by using the visual sensor network. Since the applications using visual sensors take pictures of the outdoor areas, the images may not be well contrasted due to cloudy weather or low-light time periods such as a sunset. In this paper, we first model the color characteristics according to illumination using the characteristics of visual sensors that continuously capture the same area. Using this model, a new method for improving low contrast images in real time is proposed. In order to make the model, the regions of interest consisting of the same color are set up and the changes of color according to the brightness of images are measured. The gamma function is used to model color characteristics using the measured data. It is shown by experimental results that the proposed method improves the contrast of an image by adjusting the color components of the low contrast image simply and accurately.

• 한국정보통신설비학회:학술대회논문집
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• 2005.08a
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• pp.370-373
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• 2005

건물의 무선 센서 네트워크의 개념 도입은 앞으로 도래할 유비쿼터스 환경에서 매우 비중 있는 어플리케이션으로 지능형 및 자동화 모니터링 시스템을 통해 건물의 실시간 모니터링을 함으로써 건물의 안전방지 및 온도, 습도 유지 등 여러 중요한 일을 수행할 수 있다. 본 논문에서는 빌딩에 설치된 각 센서 노드들로부터 조도의 데이터를 수집하고 비쥬얼 스튜디오 환경을 사용하여 호스트에서 모니터링을 하는 어플리케이션을 구현하여 보았다.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.175-186
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• 2018

Due to global warming, various natural disasters such as floods and localized heavy rains are increasing. If a natural disaster can be detected and analyzed in advance and effectively, it can prevent enormous damage due to natural disasters. Recent development in visual sensor technologies has encouraged various studies on monitoring environments including rivers. In this paper, we propose a method to detect river regions from river images which can be exploited for river surveillance systems using video sensor networks. In the proposed method, we first analyze the color properties of the river region and the background region of a image and then propose a way to select the proper color channel and binarize the image to detect the river region. It is shown by experimental results that the proposed method is simple but detects river regions accurately.