• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.36-54
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• 2017

The purpose of this paper is to develop a multi-sensor fusion-based traffic information acquisition system with robust to environmental changes. it combines the characteristics of each sensor and is more robust to the environmental changes than the video detector. Moreover, it is not affected by the time of day and night, and has less maintenance cost than the inductive-loop traffic detector. This is accomplished by synthesizing object tracking informations based on a radar, vehicle classification informations based on a video detector and reliable object detections of a infrared range finder. To prove the effectiveness of the proposed system, I conducted experiments for 6 hours over 5 days of the daytime and early evening on the pedestrian - accessible road. According to the experimental results, it has 88.7% classification accuracy and 95.5% vehicle detection rate. If the parameters of this system is optimized to adapt to the experimental environment changes, it is expected that it will contribute to the advancement of ITS.

• The Journal of Korea Robotics Society
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• v.5 no.2
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• pp.152-159
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• 2010

Finding a head of a person in a scene is very important for taking a well composed picture by a robot photographer because it depends on the position of the head. So in this paper, we propose a robust head tracking algorithm using a hybrid of an omega shape tracker and local binary pattern (LBP) AdaBoost face detector for the robot photographer to take a fine picture automatically. Face detection algorithms have good performance in terms of finding frontal faces, but it is not the same for rotated faces. In addition, when the face is occluded by a hat or hands, it has a hard time finding the face. In order to solve this problem, the omega shape tracker based on active shape model (ASM) is presented. The omega shape tracker is robust to occlusion and illuminationchange. However, whenthe environment is dynamic,such as when people move fast and when there is a complex background, its performance is unsatisfactory. Therefore, a method combining the face detection algorithm and the omega shape tracker by probabilistic method using histograms of oriented gradient (HOG) descriptor is proposed in this paper, in order to robustly find human head. A robot photographer was also implemented to abide by the 'rule of thirds' and to take photos when people smile.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.4
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• pp.339-345
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• 2010

This paper introduces GP(Genetic Programming) based robust corner detectors for scaled and rotated images. Various empirical algorithms have been studied to improve computational speed and accuracy including approaches, such as the Harris and SUSAN, FAST corner detectors. These techniques are highly efficient for well-defined corners, but are limited to corner-like edges which are often generated in rotated images. It is very difficult to detect correctly edges which have characteristics similar to corners. In this paper, we have focused the above challenging problem and proposed Genetic Programming-based automated generation of corner detectors which is robust to scaled and rotated images. The proposed method is compared to the existing corner detectors on test images and shows superior results.

• Journal of information and communication convergence engineering
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• v.8 no.6
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• pp.640-644
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• 2010

When we talk with hands-free in a car or noisy lobby, the performance of the echo canceller degrade because background noise added to echo caused by the distance from mouth to microphone is relatively long. It gives a reason for necessity of noise-robust and high convergence speed adaptive algorithm. And if acoustic echo canceller operated not perfectly, residual signal going through the echo canceller to far-end speaker remains residual echo, which degrade quality of talk. To solve this problem, post-processing needed to remove residual echo ones more. In this paper, we propose a new acoustic echo canceller, which has noise robust and high convergence speed, linked with linear predictor as a post-processor. By computer simulation, it is confirmed that the proposed algorithm shows better performance from acoustic interference cancellation (AIC) viewpoint.

• ETRI Journal
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• v.30 no.6
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• pp.807-817
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• 2008

We present a low-density parity-check (LDPC)-based, threaded layered space-time-frequency system with emphasis on the iterative receiver design. First, the unbiased minimum mean-squared-error iterative-tree-search (U-MMSE-ITS) detector, which is known to be one of the most efficient multi-input multi-output (MIMO) detectors available, is improved by augmentation of the partial-length paths and by the addition of one-bit complement sequences. Compared with the U-MMSE-ITS detector, the improved detector provides better detection performance with lower complexity. Furthermore, the improved detector is robust to arbitrary MIMO channels and to any antenna configurations. Second, based on the structure of the iterative receiver, we present a low-complexity belief-propagation (BP) decoding algorithm for LDPC-codes. This BP decoder not only has low computing complexity but also converges very fast (5 iterations is sufficient). With the efficient receiver employing the improved detector and the low-complexity BP decoder, the proposed system is a promising solution to high-data-rate transmission over selective-fading channels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.6A
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• pp.685-692
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• 2008

In this paper, we propose a timing recovery loop for Inmarsat mini-m system downlink receiver. Inmarsat mini-m system requires a timing recovery loop which is robust in frequency offset and has fast acquisition because Inmarsat mini-m system specification requires frequency tolerance is required of ${\pm}924$ Hz (signal bandwidth: 2.4 kHz) and acquisition time of UW (Unique Word) signal duration (15ms).Therefore, we propose a timing recovery loop which is suitable for Inmarsat mini-m system. The proposed timing recovery loop adopted noncoherent UW detector and differential ELD which applied differential UW signal for stability and fast acquisition in frequency offset environment. Simulation results show that the proposed timing recovery loop has stable operation and fast acquisition in frequency offset environment for the system.

• Proceedings of the KSPS conference
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• 2002.11a
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• pp.183-186
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• 2002

The speech detection is one of the important problems in real-time speech recognition. The accurate detection of speech boundaries is crucial to the performance of speech recognizer. In this paper, we propose a speech detector based on Mel-band selection through training. In order to show the excellence of the proposed algorithm, we compare it with a conventional one, so called, EPD-VAA (EndPoint Detector based on Voice Activity Detection). The proposed speech detector is trained in order to better extract keyword speech than other speech. EPD-VAA usually works well in high SNR but it doesn't work well any more in low SNR. But the proposed algorithm pre-selects useful bands through keyword training and decides the speech boundary according to the energy level of the sub-bands that is previously selected. The experimental result shows that the proposed algorithm outperforms the EPD-VAA.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.3
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• pp.615-622
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• 2007

In general, Harris detector is commonly used for finding salient points in watermarking systems using feature points. Harris detector is a kind of combined comer and edge detector which is based on neighboring image data distribution, therefore it has some limitation to find accurate salient points after watermark embedding or any kinds of digital attacks. In this paper, we have used cross reference points which use not data distribution but geometrical structure of a normalized image in order to avoid pointing error caused by the distortion of image data. After normalization, we find cross reference points and take inverse normalization of these points. Next, we construct a group of triangles using tessellation with inversely normalized cross reference points. The watermarks are affine transformed and transformed-watermarks are embedded into not normalized image but original one. Only locations of watermarks are determined on the normalized image. Therefore, we can reduce data loss of watermark which is caused by inverse normalization. As a result, we can detect watermarks with high correlation after several digital attacks.

• MALSORI
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• no.48
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• pp.107-116
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• 2003

This paper deals with a new parameter for voice detection which is used for many areas of speech engineering such as speech synthesis, speech recognition and speech coding. CV (Coefficient of Variation) of speech spectrum as well as other feature parameters is used for the detection of speech. CV is calculated only in the specific range of speech spectrum. Average magnitude and spectral magnitude are also employed to improve the performance of detector. From the experimental results the proposed voice detector outperformed the conventional energy-based detector in the sense of error measurements.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.5
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• pp.240-246
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• 2014

A fault detector was developed for heat exchangers of a hybrid heat pump (HP) for household. The proposed detector can be applied directly to raw operating data. It is to monitor a tracking error between a measured saturation temperature and its state observer. The observer was estimated from a state-space model simulating dynamics of a heat exchanger. The real hybrid HP was substituted with a dynamic simulator that implemented two-phased heat transfer and was validated by experimental data. And artificial fault data were generated using the simulator. Diagnosing the data showed the following. The residual calculated from the state observer error shows a relatively robust consistency with respect fouling level. The fault detector is practically useful because it detects a threshold fouling beyond which the performance starts to deteriorate significantly.