• Journal of information and communication convergence engineering
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• v.13 no.3
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• pp.197-204
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• 2015

In this paper, we present an algorithm for the detection of illegally parked vehicles based on a combination of some image processing algorithms. A digital camera is fixed in the illegal parking region to capture the video frames. An adaptive Gaussian mixture model (GMM) is used for background subtraction in a complex environment to identify the regions of moving objects in our test video. Stationary objects are detected by using the pixel-level features in time sequences. A stationary vehicle is detected by using the local features of the object, and thus, information about illegally parked vehicles is successfully obtained. An automatic alarm system can be utilized according to the different regulations of different illegal parking regions. The results of this study obtained using a test video sequence of a real-time traffic scene show that the proposed method is effective.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.2
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• pp.19-25
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• 2013

In this paper, we propose an approach to tracking road regions from video sequences. The proposed method segments and tracks road regions by utilizing the prior information from the result of the previous frame. For the efficiency of the system, we have a simple assumption that the road region is usually shown in the lower part of input images so that lower 60% of input images is set to the region of interest(ROI). After initial segmentation using flood-fill algorithm, we merge neighboring regions based on color similarity measure. The previous segmentation result, in which seed points for the successive frame are extracted, is used as prior information to segment the current frame. The similarity between the road region of the previous frame and that of the current frame is measured by the modified Jaccard coefficient. According to the similarity we refine and track the detected road regions. The experimental results reveal that the proposed method is effective to segment and track road regions in noisy and non-noisy environments.

• Journal of Korea Multimedia Society
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• v.16 no.9
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• pp.1031-1043
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• 2013

Extracting hand region from images is the first part in the process to recognize hand posture and gesture interaction. Therefore, a good segmenting method is important because it determines the overall performance of hand recognition systems. Conventional hand segmentation researches were prone to changing illumination conditions or limited to the ability to detect multiple people. In this paper, we propose a robust technique based on the fusion of skin-color data and depth information for hand segmentation process. The proposed algorithm uses skin-color data to localize accurate seed location for region-growing from a complicated background. Based on the seed location, our algorithm adjusts each detected blob to fill up the hole region. A region-growing algorithm is applied to the adjusted blob boundary at the detected depth image to obtain a robust hand region against illumination effects. Also, the resulting hand region is used to train our skin-model adaptively which further reduces the effects of changing illumination. We conducted experiments to compare our results with conventional techniques which validates the robustness of the proposed algorithm and in addition we show our method works well even in a counter light condition.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2000.04a
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• pp.36-43
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• 2000

Many formats are used for recording and processing in the research of earthquake seismology and earthquake engineering. It is very difficult to program the Reading and writing algorithm for data processing because fill formats are very different from each other. It is suggested new file format of Korea Standard earthquake data (KSED) two types of ASCII and binary that are read and written easily. The Program package of basic data processing (Analyst) which has function of basic filtering spectrum analysis event gathering phase picking and location is developed In addition this program supports file transformation from another format(Mini SEED OMD K2) to KSED format.

• Korean Journal of Optics and Photonics
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• v.33 no.6
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• pp.245-251
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• 2022

We have developed a multi-channel fiber laser for tiled laser beam combining and a laser output array system for multi-beam alignment. The fiber laser is a master oscillator power amplifier configuration that has a common seed, a preamplifier, and a 7-channel amplifier. The output power of each channel is more than 10 W. The laser output array system is a packed cylindrical configuration for a high fill-factor, and it has capabilities for collimation and tilt control with built-in PZT. Multi-beam alignment to a target is successfully implemented using PZT controlled with a stochastic parallel gradient descent (SPGD) algorithm.