• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.11
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• pp.48-56
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• 1998

In this paper, a moving object detection and face region extraction algorithm which can be used in video monitoring systems is presented. The proposed algorithm is composed of two stages. In the first stage, each frame of an input video sequence is analyzed using three measures which are based on image pixel difference. If the current frame contains moving objects, their skin regions are extracted using color and frame difference information in the second stage. Since the proposed algorithm does not rely on computationally expensive features like optical flow, it is well suited for real-time applications. Experimental results tested on various sequences have shown the robustness of the proposed algorithm.

• Journal of IKEEE
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• v.22 no.3
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• pp.558-564
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• 2018

In distributed estimation where each node can collect only partial information on the parameter of interest without communication between nodes and quantize it before transmission to a fusion node which conducts estimation of the parameter, we consider a novel quantization technique employed at local nodes. It should be noted that the performance can be greatly improved if each node can transmit its measurement to one designated node (namely, head node) which can quantize its estimate using the total rate available in the system. For this case, the best strategy at the head node would be simply to partition the parameter space using the generalized Lloyd algorithm, producing the global codewords, one of which is closest to the estimate is transmitted to a fusion node. In this paper, we propose an iterative design algorithm that seeks to efficiently assign the codewords into each of quantization partitions at nodes so as to achieve the performance close to that of the system with the head node. We show through extensive experiments that the proposed algorithm offers a performance improvement in rate-distortion perspective as compared with previous novel techniques.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.136-141
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• 2009

This paper proposed a framework for handover method in continuously tracking a person of interest across cooperative pan-tilt-zoom (PTZ) cameras. The algorithm here is based on a robust non-parametric technique for climbing density gradients to find the peak of probability distributions called the mean shift algorithm. Most tracking algorithms use only one cue (such as color). The color features are not always discriminative enough for target localization because illumination or viewpoints tend to change. Moreover the background may be of a color similar to that of the target. In our proposed system, the continuous person tracking across cooperative PTZ cameras by mean shift tracking that using color and shape histogram to be feature distributions. Color and shape distributions of interested person are used to register the target person across cameras. For the first camera, we select interested person for tracking using skin color, cloth color and boundary of body. To handover tracking process between two cameras, the second camera receives color and shape cues of a target person from the first camera and using linear color calibration to help with handover process. Our experimental results demonstrate color and shape feature in mean shift algorithm is capable for continuously and accurately track the target person across cameras.

• Journal of Auto-vehicle Safety Association
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• v.12 no.2
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• pp.33-39
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• 2020

This paper presents an Around View Monitoring (AVM) stop-line detection based longitudinal position correction algorithm for automated driving on urban roads. Poor positioning accuracy of low-cost GPS has many problems for precise path tracking. Therefore, this study aims to improve the longitudinal positioning accuracy of low-cost GPS. The algorithm has three main processes. The first process is a stop-line detection. In this process, the stop-line is detected using Hough Transform from the AVM camera. The second process is a map matching. In the map matching process, to find the corrected vehicle position, the detected line is matched to the stop-line of the HD map using the Iterative Closest Point (ICP) method. Third, longitudinal position of low-cost GPS is updated using a corrected vehicle position with Kalman Filter. The proposed algorithm is implemented in the Robot Operating System (ROS) environment and verified on the actual urban road driving data. Compared to low-cost GPS only, Test results show the longitudinal localization performance was improved.

• Journal of the Korea Institute of Military Science and Technology
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• v.5 no.2
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• pp.169-184
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• 2002

In order to extract bearing information from the directional sensors of DIFAR(directional frequency analysis and recording) that is a kind of passive sonobuoy, the cardioid beamforming algorithm applicable to DIFAR system was studied in the frequency domain. the algorithm uses narrow-band signals propagated though the media from the acoustic sources such as ship machineries. The proposed algorithm is expected to give signal to noise ratio of 6dB when it uses the maximum response axis(MRA) among the Cardioid beams. The estimated bearings agree very well with those from GPS data. Assuming the bearings from GPS data to be real values, the estimation errors are analyzed statistically. The histogram of estimation errors in each frequency have Gaussian shape, the mean and standard deviation dropping in the ranges -1.1~$6.7^{\circ}$ and 13.3~$43.6^{\circ}$, respectively. Estimation errors are caused by SMR degradation due to propagation loss between the source and receiver, daily fluctuating geo-magnetic fields, and non-stationary background noises. If multiple DIFAR systems are employed, in addition to bearing, range information could be estimated and finally localization or tracking of a target is possible.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.548-551
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• 2003

The adaptive filter is proposed for removing EOG from measured EEG on the frontal lobe. The proposed adaptive filter has been implemented and the feedback output control algorithm has been employed to control the alpha wave ratio on the basis of TMS320C31 DSP board with the on-line and real time performance. The feedback algorithm controls the input voltage of stimulating devices on the portable bio-feedback system. The EEG data are acquired at the $F_{p1}$ and $F_{p2}$ localization and are processed by the proposed adaptive filter. We demonstrated that the proposed adaptive filter could effectively remove EOG from the measured EEG on the frontal lobe and the feedback algorithm is proper to control the output voltage of DSP board using the ratio of the alpha wave.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.23-29
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• 2015

In this paper, we introduce a underwater ranging algorithm with Look-up Table (LUT) by modifying the existing method which is using the changes of angles of accoustic rays with SSP (Sound Speed Profile). We compare the horizontal distance errors and the calculation times. Our new algorithm exploits Time of Arriva l(ToA) - horizontal distance table based on SSP. This algorithm offers faster calculation speed than the previous one with the slight increase of the distance estimation error.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.10
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• pp.164-170
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• 2014

A single near-field sounde source bearing and ranging method based on a independent doublet array is proposed. In the common case of bearing estimation method, unform linear array or uniform circular array are used. It is constrained retaining aperture because of array structure to estimate the distance of the sound source. Recent using independent doublet array sound source's bearing and distance esmtimation method is proposed by wide aperture. It is limited to the case doublets are located on a straight line. In this paper, we generalize the case and estimate the localization of a sound source in the various array structure. The proposed algorithm was verified performance through simulation.

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.5
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• pp.422-429
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• 2013

It is of great importance to localize leakages in complex pipelines for assuring their safety. A sensor array that can detect where leakages occur enables us to monitor a wide area with a relatively low cost. Beamforming is a fast and efficient algorithm to estimate where sources are, but it is generally made use of in free field condition. In practice, however, many pipelines are placed in a closed space for the purpose of safety and maintenance. This leads us to take reflected waves into account to the beamforming for interior leakage localization. Beam power distribution of reflected waves in a closed space is formulated, and spatial average is introduced to suppress the effect of reflected waves. Computer simulations and experiments ensure how the proposed method is effective to localize leakage in a closed space for structural health monitoring.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.4
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• pp.992-999
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• 2014

This paper presents an extensive experimental comparison of a variety of multi-label learning methods for the accurate prediction of subcellular localization of proteins which simultaneously exist at multiple subcellular locations. We compared several methods from three categories of multi-label classification algorithms: algorithm adaptation, problem transformation, and meta learning. Experimental results are analyzed using 12 multi-label evaluation measures to assess the behavior of the methods from a variety of view-points. We also use a new summarization measure to find the best performing method. Experimental results show that the best performing methods are power-set method pruning a infrequently occurring subsets of labels and classifier chains modeling relevant labels with an additional feature. futhermore, ensembles of many classifiers of these methods enhance the performance further. The recommendation from this study is that the correlation of subcellular locations is an effective clue for classification, this is because the subcellular locations of proteins performing certain biological function are not independent but correlated.