• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.30-36
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• 2006

In this paper, a new type of written image segmentation based on relative comparison of region areas is proposed. The original image is composed of two distinctive regions; information and background. Compared with this binary original image, the observed one is the gray scale which is represented with complex regions with speckles and noise due to degradation or contamination. For applying threshold or statistical approach, there occurs the region-deformation problem in the process of binarization. At first step, the efficient iterated conditional mode (ICM) which takes the lozenge type block is used for regions formation into the binary image. Secondly the information region is estimated through selecting action and restored its primary state. Not only decision of the attachment to a region but also the calculation of the magnitude of its area are carried on at each current pixel iteratively. All region areas are sorted into a set and selected through the decision parameter which is obtained statistically. Our experiments show that these approaches are effective on ink-rubbed copy image (拓本 'Takbon') and efficient at shape restoration. Experiments on gray scale image show promising shape extraction results, comparing with the threshold-segmentation and conventional ICM method.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.4
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• pp.283-288
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• 2001

In this paper, we proposed a method for extracting facial characteristics of human being in an image. Given a pair of gray level sample images taken with and without human being, the face of human being is segmented from the image. Noise in the input images is removed with the help of Gaussian filters. Edge maps are found of the two input images. The binary edge differential image is obtained from the difference of the two input edge maps. A mask for face detection is made from the process of erosion followed by dilation on the resulting binary edge differential image. This mask is used to extract the human being from the two input image sequences. Features of face are extracted from the segmented image. An effective recognition system using the discrete wave let transform (DWT) is used for recognition. For extracting the facial features, such as eyebrows, eyes, nose and mouth, edge detector is applied on the segmented face image. The area of eye and the center of face are found from horizontal and vertical components of the edge map of the segmented image. other facial features are obtained from edge information of the image. The characteristic vectors are extrated from DWT of the segmented face image. These characteristic vectors are normalized between +1 and -1, and are used as input vectors for the neural network. Simulation results show recognition rate of 100% on the learned system, and about 92% on the test images.

• Korean Journal of Optics and Photonics
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• v.18 no.3
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• pp.202-207
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• 2007

Optical visual cryptography (OVC) based on binary computer generated holograms (BCGH) is proposed. OVC used optics instead of human eyesight for decryption of visual cryptography (VC). As a result, it was possible to adapt cryptography to an optical system. However, it also had some difficulties because it did not overcome the existing problems of VC completely. This paper suggests a method of optical cryptography implementation based on the phase modulation characteristics of a liquid crystal display (LCD). The problems are evaluated by simulation. This system shows that the noise is reduced and resolution is improved compared with the conventional OVC.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.11
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• pp.637-644
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• 2014

This paper investigates the detection performance of fault location using STDR(sequence time domain reflectometry) and SSTDR(spread spectrum time domain reflectometry) with various length and types of sequences, and then, proposes an improved detection technique by eliminating the injected signal in SSTDR. The detection error rates are compared and analyzed in power line channel model with various fault locations, fault types, and spreading sequences such as m-sequence, binary Barker sequence, and 4-phase Frank sequence. It is shown that the proposed technique is able to improve the detection performance obviously when the reflected signal is weak or the fault location is extremely close.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.3
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• pp.181-189
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• 2004

This paper describes the method for detecting vehicles in the rear and rear-side at night by using headlight features. A headlight is the outstanding feature that can be used to discriminate a vehicle from a dark background. In the segmentation process, a night image is transformed to a binary image that consists of black background and white regions by gray-level thresholding, and noise in the binary image is eliminated by a morphological operation. In the feature extraction process, the geometric features and moment invariant features of a headlight are defined, and they are measured in each segmented region. Regions that are not appropriate to a headlight are filtered by using geometric feature measurement. In region classification, a pair of headlights is detected by using relational features based on the symmetry of a pair of headlights. Experimental results show that this method is very applicable to an approaching vehicle detection system at nighttime.

• Journal of Korea Multimedia Society
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• v.14 no.5
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• pp.614-621
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• 2011

This paper presents design of a wide tuning range digitally controlled oscillator(DCO) for Mobile-DTV applications. DCO is the key element of the ADPLL block that generates oscillation frequencies. We proposed a binary delay chain(BDC) structure, for wide tuning range DCO, modifying conventional fixed delay chain. The proposed structure generates oscillation frequencies by delay cell combination which has a variable delay time of $2^i$ in the range of $0{\leq}i{\leq}n-1$. The BOC structure can reduce the number of delay cells because it make possible to select delay cell and resolution. We simulated the proposed DCO by Cadence's Spectre RF tool in 1.8V chartered $0.18{\mu}m$ CMOS process. The simulation results showed 77MHz~2.07GHz frequency range and 3ps resolution. The phase noise yields -101dBc/Hz@1MHz at Mobile-DTV maximum frequency 1675MHz and the power consumption is 5.87mW. The proposed DCO satisfies Mobile-DTV standards such as ATSC-M/H, DVB-H, ISDB-T, T-DMB.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.3
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• pp.339-349
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• 2017

This paper proposes a four-stage algorithm for detecting lanes on a driving car. In the first stage, it extracts region of interests in an image. In the second stage, it employs a median filter to remove noise. In the third stage, a binary algorithm is used to classify two classes of backgrond and foreground of an input image. Finally, an image erosion algorithm is utilized to obtain clear lanes by removing noises and edges remained after the binary process. However, the proposed lane detection algorithm requires high computational time. To address this issue, this paper presents a parallel implementation of a real-time line detection algorithm on a multi-core architecture. In addition, we implement and simulate 8 different processing element (PE) architectures to select an optimal PE architecture for the target application. Experimental results indicate that 40×40 PE architecture show the best performance, energy efficiency and area efficiency.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.184-191
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• 2022

Underwater acoustic wave in shallow water is propagated through multipath that has a large delay spread causing Inter-Symbol Interference (ISI) and these characteristics deteriorate the performance in the communication system. In order to analyze the communication performance and investigate the correlation with multipath delay spread in a reverberant environment, an underwater acoustic communication experiment using Binary Phase-Shift Keying (BPSK) signals with symbol rates from 100 sym/s to 8000 sym/s was conducted in a 5 × 5 × 5 m³ water tank. The acoustic channels in a well-controlled tank environment had the characteristics of dense multipath delay spread due to multiple reflections from the interfaces and walls within the tank and showed the maximum excess delay of 40 ms or less, and the Root Mean Squared (RMS) delay spread of 8 ms or less. In this paper, the performances of Bit Error Rate (BER) and output Signal-to-Noise Ratio (SNR) were analyzed using four types of communication demodulation techniques. And the parameter, Symbol interval to Delay spread Ratio in reverberant environment (SDR_rev), which is the ratio of symbol interval to RMS delay spread in the reverberant environment is defined. Finally, the SDR_rev was compared to the BER and the output SNR. The results present the reference symbol rate in which high communication performance can be guaranteed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.2
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• pp.179-190
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• 2001

In this proposed study, observing and analyzing contrast enhanced abdominal CT images, we segmented the liver automatically. We computed the ratio of each gray value from the estimated gray value range. With the average value of mesh image, we distinguished the liver from the noise parts. We divided the region based on immersion simulation. The threshold value is determined from the mesh image which is generated from each gray value portion of the liver and is used in dividing the liver to the noise region. To get the outline of the liver, we generated template image which represents the lump of the liver, and subtracted it from the binary image. With the results we use the proposed algorithm using 8-connectivity instead of the present opening algorithm, to reduce the processing time. We computed the volume from the segmented organ size and presented a clinical demonstration with the animal experiment

• The Journal of the Korea Contents Association
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• v.14 no.5
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• pp.425-435
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• 2014

The research for extracting man-made features such as building and road from the aerial photograph or satellite imagery has been performed actively. As lately the resolution of digital aerial photographs was improved, unwanted features(noise) would be often detected. An edge detection algorithm is developed to make up for such a noise problem, make boundaries of wanted objects clear and extract only needed features. The algorithm developed in this research performs separating RGB channels, differencing between channels, transforming in to binary images, excluding noises and restoring shapes, and edge extraction in order. The images to be used for edge detection are prepared through bundle adjustment, DTM extraction, orthorectification and mosaicking. The roof edges of small building on preprocessed digital aerial orthophotos were extracted using the algorithm developed in this study. The validity of the algorithms was proved by comparing edge results of small building extracted in this study with those of conventional methods.