• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.463-470
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• 2006

It is difficult to track and extract the movement of an object through a camera exactly because of noises and changes of the light. The fast searching algorithm is necessary to extract the object and to track the movement for realtime image. In this paper, we propose the correct and fast algorithm using the variable searching area and the background image change method to robustic for the change of background image. In case the threshold value is smaller than reference value on an experimental basis, change the background image. When it is bigger, we decide it is the point of the time of the object input and then extract boundary point of it through the pixel check. The extracted boundary points detect precise movement of the object by creating area block of it and searching block that maintaining distance. The designed and embodied system shows more than 95% accuracy in the experimental results.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.1
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• pp.49-57
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• 2005

The proposed algorithm is to achieve the robust optical flow detection which is applicable for the case that the outlier rate is over 80%. If the outlier rate of optical flows is over 30%, the discrimination between the inliers and outlier with the conventional algorithm is very difficult. The proposed algorithm is to overcome such difficulty with three steps of grouping algorithm; 1) constructing the 2D histogram with two axies of the lengths and the directions of optical flows. 2) sorting the number of optical flows in each bin of the two-dimensional histogram in the descending order and removing some bins with lower number of optical flows than threshold. 3) increasing the resolution of the two-dimensional histogram if the number of optical flows in a specific bin is over 20% and decreasing the resolution if the number of optical flows is less than 10%. Such processing is repeated until the number of optical flows falls into the range of 10%-20% in all the bins. The proposed algorithm works well on the different kinds of images with many of wrong optical flows. Experimental results are included.

• Journal of Satellite, Information and Communications
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• v.11 no.4
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• pp.58-62
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• 2016

In this paper, we propose a pre-processing scheme for improving indoor positioning accuracy in impulsive noise channel environments. The impulsive noise can be generated by multi-path fading effects by complicated indoor structures or interference environments, which causes an increase in demodulation error probability. The proposed pre-processing scheme is performed before a triangulation method to calculate user's position, and providing reliable input data demodulated from a received signal to the triangulation method. Therefore, we studied and proposed an adaptive threshold function for mitigation of the impulsive noise based on wavelet denoising. Through results of computer simulations for the proposed scheme, we confirmed that Bit Error Rate and Signal-to-Noise Ratio performance is improved compared to conventional schemes.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.51-64
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• 2005

The proposed algorithm is to achieve the robust optical flow detection which is applicable for the case that the outlier rate is over $80\%$. If the outlier rate of optical flows is over $30\%$, the discrimination between the inliers and outlier with the conventional algorithm is very difficult. The proposed algorithm is to overcome such difficulty withthree steps of grouping algorithm; 1) constructing the 2 D histogram with two axies of the lengths and the directions of optical flows. 2) sorting the number of optical flows in each bin of the two-dimensional histogram in the descendingorder and removing some bins with lower number of optical flows than threshold 3) increasing the resolution of the two-dimensional histogram if the number of optical flows in a specific bin is over $20\%$ and decreasing theresolution if the number of optical flows is less than $10\%$. Such processing is repeated until the the number of optical flows falls into the range of $10\%-20\%$ in all the bins. The proposed algorithm works well on the different kinds of images with many of wrong optical flows. Experimental results are included.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.73-79
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• 2014

In this paper, we proposed the mechanism which can measure traffic flow and vehicle speed on the highway as well as road by using the video and image processing to detect and track cars in a video sequence. The proposed mechanism uses the first few frames of the video stream to estimate the background image. The visual tracking system is a simple algorithm based on the sum of absolute frame difference. It subtracts the background from each video frame to produce foreground images. By thresholding and performing morphological closing on each foreground image, the proposed mechanism produces binary feature images, which are shown in the threshold window. By measuring the distance between the "first white line" mark and the "second white line"mark proceeding, it is possible to find the car's position. Average velocity is defined as the change in position of an object divided by the time over which the change takes place. The results of proposed mechanism agree well with the measured data, and view the results in real time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.476-483
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• 2009

Tracking and detecting targets by the microwave seeker is affected by the clutter reflecting from the earth's surface. In order to detect retreating targets in look-down scenario, which appear in the sidelobe clutter (SLC) region, in the microwave seeker of high pulse repetition frequency (HPRF) mode, it is necessary to understand statistical characteristics of the surface SLC. Statistical analysis of SLC has been conducted for several kinds of the surface using data obtained by the captive flight test of the microwave seeker in the HPRF mode. The probability density function (PDF) fitting is conducted for several kinds and conditions of the surface. PDFs and PDF parameters, which best describe statistical distribution of the SLC power, are estimated. By using the estimated PDFs and PDF parameters, analyses for setting the target-detection thresholds, which give a desired level of target-detection false alarm probability, are made. These analysis materials for statistical characteristics of SLC power and the target-detection threshold can be used in various fields, such as development of a target-detection method, the constant false alarm rate processing.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.21 no.1
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• pp.55-71
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• 2018

To improve the ecological function of urban areas, the guideline for applying the Biotope Area Ratio to the Environmental Impact Assessment (EIA) was developed in 2005 and modified in the July, 2017. This study investigates whether the guideline has been actually practiced in the real world by searching reports including 648 cases of the Strategic Environmental Impact Assessment (SEIA) and 471 cases of the EIA. The results show that the 38% of SEIA and the 43% of EIA include sections about Biotope Area Ratio, and the 15% of SEIA and the 25 % of EIA are satisfied the threshold of the Biotope Area Ratio suggested by the guideline. The statistical analysis results show that this low level of practice was not improved through the modification of the guideline in 2017. This is because the guideline is forcibleness, its explanation is unclear, and stockholders' understanding of it lacks. In addition, lack of tracking management on SEIA and EIA also contributes to the low level of practice of the guideline. To promote the practice, the efforts to legislate and publicize the guideline are required.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.229-234
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• 2006

Acquisition is to detect the presence of the GPS signal. Once the signal is detected, the estimated frequency and code phase are passed to a tracking loop to demodulate the navigation data. In order to detect the weak signal, multiple length of data integration is always needed. In this paper, we present five different acquisition approaches based on circular correlation and Fast Fourier Transform (FFT), using coherent as well as non-coherent integration techniques for the multiple length of collected GPS satellite signal. Moreover a general approach of determining the acquisition threshold is introduced based on noise distribution which has been proved effective, and independent of the hardware. In the end of this paper, the processing speed and acquisition gain of each method are illustrated, compared, and analyzed. The results show that coherent approach is much more time consuming compared to noncoherent approaches, and in the case of multiple length of data integration from 2ms to 8ms, the processing times consumed by the fastest non-coherent acquisition method are only 25.87% to 1.52% in a single search, and 34.76% to 1.06% in a global search of those in the coherent acquisition. However, coherent acquisition also demonstrates its better performance in the acquisition gain, and in the case of 8ms of data integration it is 4.23 to 4.41 dB higher than that in the non-coherent approaches. Finally, an applicable scheme of combining coherent and non-coherent acquisition approaches in the development of a real-time Software GPS receiver in the University of Tokyo is provided.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.6
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• pp.1153-1158
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• 2006

The classification of the background and cell areas is very important research area because of the ambiguous boundary. In this paper, the region of cell is extracted from an image of uterine cervical cytodiagnosis using the region growing method that increases the region of interest based on similarity between pixels. Segmented image from background and cell areas is binarized using a threshold value. And then 8-directional tracking algorithm for contour lines is applied to extract the cell area. First, the extracted nucleus is transformed to RGB color that is the original image. Second, the K-means clustering algorithm is employed to classify RGB pixels to the R, G, and B channels, respectively. Third, the Hue information of nucleus is extracted from the HSI models that is the transformation of the clustering values in R, G, and B channels. The backpropagation algorithm is employed to classify and identify the normal or abnormal nucleus.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4292-4307
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• 2021

For the research field of night infrared surveillance video, the target imaging in the video is easily affected by the light due to the characteristics of the active infrared camera and the classical ViBe algorithm has some problems for moving target extraction because of background misjudgment, noise interference, ghost shadow and so on. Therefore, an improved ViBe algorithm (I-ViBe) for moving target extraction in night infrared surveillance video is proposed in this paper. Firstly, the video frames are sampled and judged by the degree of light influence, and the video frame is divided into three situations: no light change, small light change, and severe light change. Secondly, the ViBe algorithm is extracted the moving target when there is no light change. The segmentation factor of the ViBe algorithm is adaptively changed to reduce the impact of the light on the ViBe algorithm when the light change is small. The moving target is extracted using the region growing algorithm improved by the image entropy in the differential image of the current frame and the background model when the illumination changes drastically. Based on the results of the simulation, the I-ViBe algorithm proposed has better robustness to the influence of illumination. When extracting moving targets at night the I-ViBe algorithm can make target extraction more accurate and provide more effective data for further night behavior recognition and target tracking.