• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4C
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• pp.401-410
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• 2007

In this paper, we propose water quality monitoring system using vision camera and multiple objects tracking method. The proposed system analyzes object individually using vision camera unlike monitoring system using sensor method. The system using vision camera consists of individual object segmentation part and objects tracking part based on interrelation between successive frames. For real-time processing, we make background image using non-parametric estimation and extract objects using background image. If we use non-parametric estimation, objects extraction method can reduce large amount of computation complexity, as well as extract objects more effectively. Multiple objects tracking method predicts next motion using moving direction, velocity and acceleration of individual object then carries out tracking based on the predicted motion. And we apply exception handling algorithms to improve tracking performance. From experiment results under various conditions, it shows that the proposed system can be available for real-time water quality monitoring system since it has very short processing time and correct multiple objects tracking.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.10
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• pp.66-74
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• 2008

Surveillance system using active tracking camera has no distance limitation of surveillance range compared to supersonic or sound sensors. However, complex motion tracking algorithm requires huge amount of computation. Compared to conventional methods using DSPs or embedded processors, this paper proposes and implements a novel motion tracker unit that detects and extracts motion information of moving objects by using picture difference of consecutive frames. The proposed motion tracker unit was implemented in FPGA with about 13,000 gates. It processes NTSC format video and was verified by embedding it into the active surveillance camera system. We also propose and implements a motion estimator unit linkable to video codec by embedding the proposed motion tracker unit into ready-made motion estimator unit. The implemented motion estimator unit is about 17,000 gates in $0.35{\mu}m$ process.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.87-97
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• 2018

Rainfall depth is an important meteorological information. Generally, high spatial resolution rainfall data such as road-level rainfall data are more beneficial. However, it is expensive to set up sufficient Automatic Weather Systems to get the road-level rainfall data. In this paper, we proposed to use deep learning to recognize rainfall depth from road surveillance videos. To achieve this goal, we collected two new video datasets, and proposed a new deep learning architecture named Temporal and Spatial Segment Networks (TSSN) for rainfall depth recognition. Under TSSN, the experimental results show that the combination of the video frame and the differential frame is a superior solution for the rainfall depth recognition. Also, the proposed TSSN architecture outperforms other architectures implemented in this paper.

• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.1-14
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• 2024

Global navigation satellite system (GNSS) providing position, navigation and timing (PNT) services consist of satellite, ground, and user systems. Monitoring stations, a key element of the ground segment, play a crucial role in continuously collecting satellite navigation signals for service provision and fault detection. These stations detect anomalies such as threats to the signal-in-space (SIS) of satellites, receiver issues, and local threats. They deliver received data and detection results to the master station. This paper introduces the main monitoring algorithms and measurement pre-processing processes for quality assessment and fault detection of received satellite signals in current satellite navigation system monitoring stations. Furthermore, it proposes a strategy for the development of components, architecture, and algorithms for the new regional navigation satellite system (RNSS) monitoring stations.

• Journal of Broadcast Engineering
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• v.7 no.2
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• pp.181-191
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• 2002

Video based surveillance systems based on an active camera require a fast algorithm for real time detection and tracking of local motion in the presence of global motion. This paper presents a new fast and efficient motion detection and tracking algorithm using the displaced frame difference (DFD). In the Proposed algorithm, first, a Previous frame is adaptively selected according to the magnitude of object motion, and the global motion is estimated by using only a few confident matching blocks for a fast and accurate result. Then, a DFD is obtained between the current frame and the selected previous frame displaced by the global motion. Finally, a moving object is extracted from the noisy DFD by utilizing the correlation between the DFD and current frame. We implement this algorithm into an active camera system including a pan-tilt unit and a standard PC equipped with an AMD 800MHz processor. The system can perform the exhaustive search for a search range of 120, and achieve the processing speed of about 50 frames/sec for video sequences of 320$\times$240. Thereby, it provides satisfactory tracking results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.4
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• pp.1777-1783
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• 2012

In this paper, a new motor driving circuit is designed to improve the output performance of DC motor, and a controller is developed with the designed circuit. By the designed driving circuit, a controller can continuously drive DC motors by a transformer which has switching signals of a self-generated circuit to operate it. And while the DC motor have a maximum velocity, the reference voltage can be maintained higher value than that of triangle voltage and it makes the DC motor driving transistor ON and maximum power. A 24V-500W DC motor controller is developed with the proposed motor driving circuit, and also a small electric car is made and the driving test of it is executed. The test results shows that it can continuously control go and back speed of motor with 12A driving current. And also, it is verified that the over current and heat detecting function is operating correctly and the rest value of the used battery can be displayed as 6 step from 20 to 100%.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.515-524
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• 2006

Background extraction is an important technique to find the moving objects in video surveillance system. This paper proposes a new on-line background extraction method for color video using vector order statistics. In the proposed method, using the fact that background occurs more frequently than objects, the vector median of color pixels in consecutive frames Is treated as background at the position. Also, the objects of current frame are consisted of the set of pixels whose distance from background pixel is larger than threshold. In the paper, the proposed method is compared with the on-line multiple background extraction based on Gaussian mixture model(GMM) in order to evaluate the performance. As the result, its performance is similar or superior to the method based on GMM.

• Journal of Radiation Protection and Research
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• v.33 no.3
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• pp.121-126
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• 2008

Radioactivities of the stack air effluents from the Advance Fuel Science Building (AFSB) at KAERI have been investigated and evaluated. In this AFSB, nuclear fuels for the HANARO research reactor have been fabricated and the advanced nuclear fuels have been studied. A stack air monitoring system has been continuously operating to monitor the stack air effluents from the facility to protect the environment. As the results of the periodical radioactivity measurement and both the gamma and alpha spectrometry for the millipore filters taken from the stack air monitor from January until March 2008, a trace amount of primordial $^{40}K$ and the short-lived decay products of natural borne $^{222}Rn$ and $^{220}Rn$ have been detected. However, the radioactivities have rapidly decayed to the level below the Minimum Detectable Activity (MDA) of the counting system. Therefore, it was evaluated that no uranium isotopes have been released to the atmosphere from the stack of the AFSB at KAERI.

• Journal of Advanced Navigation Technology
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• v.23 no.6
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• pp.554-560
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• 2019

Excore Nuclear Flux Monitoring System in Nuclear Power Plant monitors continuous reactor power up to maximum 200%. The monitoring method, however, has to be different depending on the reactor power level. Because the logarithmic pulse signals must be counted and processed exactly due to large uncertainty if their levels are low, on the other hand, they must be processed through statistical methodolgies if theirs are high to get exact monitoring values, in point of thermal degradation view. Therefore, we developed thermal degradation input signal selection circuit to transfer low level reactor power monitoring circuit to high level reactor power circuit at rated value in this paper. We proved their validities through testing them using real data used in nuclear power plant and analyzed their results. And, These methods will be used to measure the neutron level of excore nuclear flux monitoring system in nuclear power plant.

• Korean Journal of Remote Sensing
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• v.25 no.2
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• pp.95-105
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• 2009

Irregular temporal sampling is a common feature of geophysical and biological time series in remote sensing. This study proposes an on-line system for reconstructing observation image series including bad or missing observation that result from mechanical problems or sensing environmental condition. The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. An adaptive feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. In this study, the Normalized Difference Vegetation Index (NDVI) image was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula, and the adaptive reconstruction of harmonic model was then applied to the NDVI time series from 1996 to 2000 for tracking changes on the ground vegetation. The results show that the adaptive approach is potentially very effective for continuously monitoring changes on near-real time.