• Journal of Advanced Marine Engineering and Technology
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• v.37 no.8
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• pp.918-931
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• 2013

The conventional object tracking techniques using PTZ camera detects object movements by analyzing acquired image. However, this technique requires expensive hardware devices to perform a complex image processing. And it is occasionally hard to detect object movements, if an acquired image is low quality or image acquisition is impossible. In this paper, we proposes a smart security CCTV system applying to wireless sensor network technique based on IEEE 802.15.4 standard to overcome the problems of conventional object tracking technique, which enables to track suspicious objects by detecting object movements and GPS data in sensor node. This system enables an efficient control of PTZ camera to observe a wide area, decreasing image processing complexity. Also, wireless sensor network is implemented using mesh networks to increase the efficiency of installing sensor node.

• The Journal of the Acoustical Society of Korea
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• v.10 no.1
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• pp.20-29
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• 1991

A fundamental assumption in conventional linear predictive coding (LPC) analysis procedure is that the input to an all-pole vocal tract filter is white process. In the case of periodic inputs, however, a pitch bias error is introduced into the conventional LP coefficient. Multi-pulse (MP) LP analysis can reduce this bias, provided that an estimate of the excitation is available. Since the prediction error of conventional LP analysis can be modeled as the sum of an MP excitation sequence and a random noise sequence, we can view extracting MP sequences from the prediction error as a classical detection and estimation problem. In this paper, we propose an algorithm in which the locations and amplitudes of the MP sequences are first obtained by applying a likelihood ratio test (LRT) to the prediction error, and LP coefficients free of pitch bias are then obtained from the MP sequences. To verify the performance enhancement, we iterate the above procedure with adaptive threshold at each step.

• The KIPS Transactions:PartB
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• v.10B no.2
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• pp.189-196
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• 2003

This paper describes an error resilient video data transmission method using information hiding. In order to localize transmission errors in receiver, video encoder embeds one bit for a macro block during encoding process. Embedded information is detected during decoding process in the receiver, and the transmission errors can be localized by comparing the original embedding data. The localized transmission errors can be easily corrected, thus the degradation in a reconstructed image can be alleviated. Futhermore, the embedded information can be applied to protect intellectual property rights of the video data. Experimental results for 3 QCIF sized video sequenced composed of 150 frames respectively show that, while degradation in video streams in which the information is embedded is negligible, especially in a noisy channel, the average PSNR of reconstructed images can be improved about 5 dB by using embedded information. Also, intellectual property rights information can be effectively obtained from reconstructed images.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.81-88
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• 2007

We implement automobile license plates recognition system. These days automobile license plate recognition systems are widely used for tracing stolen cars. managing parking facilities, ticketing speeding cars, and so on. Recognition systems largely consist of three parts plates extraction, segments extraction, and segment recognition. For plates extraction, we measure the degree of inclination of plate. We use filters that extract only the horizontal components of the front of an automobile to measure the degree of inclination. For segment extraction, we trace the change of the number of blocks that consist solely of foreground pixels or background pixels as the horizontal scanning line moves along upward. For recognition of each individual letter or digit, we devise a variant of template matching method, called comparative template matching. Through experiments, we show that comparative template matching is less prone misled by noises and exhibits higher performance compared to the traditional method of template matching or histogram based recognition.

• The KIPS Transactions:PartB
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• v.19B no.2
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• pp.107-112
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• 2012

An active object tracking algorithm using Pan and Tilt camera based in the stepwise application of region and color information from realtime image sequences is proposed. To reduce environment noises in input sequences, Gaussian filtering is performed first. An image is divided into background and objects by using the adaptive Gaussian mixture model. Once the target object is detected, an initial search window close to an object region is set up and color information is extracted from the region. We track moving objects in realtime by using the CAMShift algorithm which enables to trace objects in active camera with the color information. The proper tracking is accomplished by controlling the amount of pan and tilt to be placed the center position of object into the middle of field of view. The experimental results show that the proposed method is more effective than the hand-operated window method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8C
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• pp.788-799
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• 2007

This paper presents a watermarking method for copyright protection and illegal copy prevention of mobile 3D contents. The proposed method embeds copyright information and user's phone number into spatial domain and encryption domain of mobile animation data based on Buyer-Seller watermarking protocol. Furthermore, we insert user's operation key so that only authorized user can play 3D animation game in mobile device. We implemented the proposed method by using mobile animation tool, G3-SDK. From experimental results, we verified that the proposed method is capable of copyright protection and illegal copy prevention since the watermark can be well extracted against geometrical attacks, such as noise addition, data accuracy variableness and data up/down scaling.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.1
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• pp.49-59
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• 2009

In this paper a watermarking algorithm is proposed to optimize the capacity of the digital watermark insertion in an experimental threshold using the characteristics of human visual system(HVS), adaptive scale factors, and weight functions based on discrete wavelet transform. After the original image is decomposed by a 3-level discrete wavelet transform, the watermarks for capacity optimization are inserted into all subbands except the baseband, by applying the important coefficients from the experimental threshold in the wavelet region. The adaptive scale factors and weight functions based on HVS are considered for the capacity optimization of the digital watermark insertion in order to enhance the robustness and invisibility. The watermarks are consisted of gaussian random sequences and detected by correlation. The experimental results showed that this algorithm can preserve a fine image quality against various attacks such as the JPEG lossy compression, noise addition, cropping, blurring, sharpening, linear and non-linear filtering, etc.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.478-484
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• 2009

Automatic speech recognition(ASR) is attractive technique in trend these day that seek convenient life. Although many approaches have been proposed for ASR but the performance is still not good in noisy environment. Now-a-days in the state of art in speech recognition, ASR uses not only the audio information but also the visual information. In this paper, We present a novel lip detection method for visual speech recognition in mobile environment. In order to apply visual information to speech recognition, we need to extract exact lip regions. Because eye-detection is more easy than lip-detection, we firstly detect positions of left and right eyes, then locate lip region roughly. After that we apply K-means clustering technique to devide that region into groups, than two lip corners and lip center are detected by choosing biggest one among clustered groups. Finally, we have shown the effectiveness of the proposed method through the experiments based on samsung AVSR database.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1B
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• pp.183-192
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• 2000

In this paper, the dual looped CMOS PLL with 3-250MHz input locking range at a single 13.3V is designed. This paper proposed a new PLL architecture with a current pumping algorithm to improve voltage-to-frequencylinearity of VCO(Voltage Controlled Oscillator). The designed VCO operates at a wide frequency range of75.8MHz-lGHz with a high linearity. Also, PFD(Phase frequency Detector) circuit preventing voltage fluctuation of the charge pump with loop filter circuit under the locked condition is designed. The simulation results of the PLL using 0.6 um N-well single poly triple metal CMOS technology illustrate a locking time of 3.5 us, a power dissipation of 92mW at 1GHz operating frequency with 125MHz of input frequency. Measured results show that the phase noise of VCO with V-I converter is -100.3dBc/Hz at a 100kHz offset frequency.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.77-82
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• 2007

In this paper, we proposed the image processing techniques for extracting the cracks in a concrete surface crack image and the enhanced Max-Min neural network for recognizing the directions of the extracted cracks. The image processing techniques used are the closing operation or morphological techniques, the Sobel masking for extracting for edges of the cracks, and the iterated binarization for acquiring the binarized image from the crack image. The cracks are extracted from the concrete surface image after applying two times of noise reduction to the binarized image. We proposed the method for automatically recognizing the directions of the cracks with the enhanced Max-Min neural network. Also, we propose an enhanced Max-Min neural network by auto-tuning of learning rate using delta-bar-delta algorithm. The experiments using real concrete crack images showed that the cracks in the concrete crack images were effectively extracted and the enhanced Max-Min neural network was effective in the recognition of direction of the extracted cracks.