• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.67-72
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• 2021

This paper compare the adative equalization performance of the DSE-MMA (Dithered Signed-Error MMA) and QE-MMA (Quantized-Error MMA) which has a simplifies the computational operation of currently used MMA algorithm. The DSE-MMA possible to improve the rubustness to noise by using the dithered signal consider the polarity of error signal in the multiplication part. In QE-MMA, it use the polarity of error signal after performing the nonlinear power-of-two quantizing operation for easiness of H/W implementation. The same channel environment was applied, and it's performance of the output signal constellation, the residual isi and maximum distortion and MSE that means the convergence characteristics, the SER that means the robustness of external noise of algorithm were compared and evaluated. As a result of computer simulation, the QE-MMA has more good in constellation, residual isi, maximum distortion, MSE performanc than DSE-MMA. In SER, the DSE-MMA has more robust due to dither signal than QE-MMA.

• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.455-462
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• 2013

This paper introduces the Spatially Preprocessed Speech Distortion Weighted Multi-channel Wiener Filter (SP-SDW-MWF) for multi-microphone noise reduction and proposes a method to determine the speech distortion weights. The SP-SDW-MWF is known as a robust noise reduction algorithm against the error caused by the mismatch in microphones. The SP-SDW-MWF adopts weights which determine the amount of noise reduction at the expense of introducing speech distortion in the noise-suppressed speech. In this paper, we use the error of power spectral density between the estimated signal and the desired signal as the evaluation measure. Thus the a priori SNR is used to control the speech distortion weights in the frequency domain. In the experimental results, the proposed method yields better result in terms of MFCC distortion compared to the conventional method.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.4
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• pp.180-186
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• 2012

In this paper, a method of edge detection from low contrast and noisy images which contain hexagonal shape is proposed. This method is based on the combination of laplacian gaussian filter and an idea of filters which are dependent on the shape. First, an algorithm which has six masks as its extractors to detect the hexagonal edges especially in the comers is used. Here, two tricom filters are used to detect the tricom joints of hexagons and other four masks are used to enhance the line segments of hexagonal edges. As a natural image, a corneal endothelial cell image which usually has a regular hexagonal shape is selected. The edge detection of hexagonal shapes in this corneal endothelial cell is important for clinical diagnosis. Next, The proposal algorithm and other conventional methods are applied to noisy hexagonal images to evaluate each efficiency. As a result, this proposal algorithm shows a robustness against noises and better detection ability in the aspects of the signal to noise ratio, the edge coineidence ratio and the detection accuracy factor as compared with other conventional methods.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.1
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• pp.38-46
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• 2004

Image segmentation is the task which partitions the image into meaningful regions and considered to be one of the most important steps in computer vision and image processing. Image segmentation is also widely used in object-based video compression such as MPEG-4 to extract out the object regions from the given frame. Watershed algorithm is frequently used to obtain the more accurate region boundaries. But, it is well known that the watershed algorithm is extremely sensitive to gradient noise and usually results in oversegmentation. To solve such a problem, we propose an image segmentation method which is robust to noise by using stabilized inverse diffusion equation (SIDE) and is more efficient in segmentation by employing multiresolution approach. In this paper, we apply both the region projection method using labels of adjacent regions and the region merging method based on region adjacency graph (RAG). Experimental results on noisy image show that the oversegmenation is reduced and segmentation efficiency is increased.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.3
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• pp.37-46
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• 2012

In RADAR and SONAR detection systems, noise environment can be classified into homogeneous and heterogeneous environment. Especially heterogeneous environments are modelled as target masking and clutter edge. Since the variability-index (VI) CFAR, a composed CFAR algorithm, dynamically selects one of the mean-level algorithms based on the VI and the MR (mean ratio) test, it is robust to various environments. However, the VI CFAR still suffers from lowered detection probabilities in heterogeneous environments. To overcome these problems, we propose an improved VI CFAR processor where TM (trimmed mean) CFAR and a sub-windowing technique are introduced to minimize the degradation of the detection probabilities appeared in heterogeneous environments. Computer simulation results show that the proposed method has the better performance in terms of detection probability and false alarm probability compared to the VI CFAR and single CFAR algorithms.

• Journal of Biomedical Engineering Research
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• v.25 no.2
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• pp.111-117
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• 2004

Most of digital subtraction methods in dental radiography are based on registration using manual landmarks. We have developed an automatic registration method without using the manual selection of landmarks. By restricting a geometrical matching of images to a region of interest (ROl), we compare the cross-correlation coefficient only between the ROIs. The affine or perspective transform parameters satisfying maximum of cross-correlation between the local regions are searched iteratively by a fast searching strategy. The parameters are searched on the 1/4 scale image coarsely and then, the fine registration is performed on the original scale image. The developed method can match the images corrupted by Gaussian noise with the same accuracy for the images without any transform simulation. The registration accuracy of the perspective method shows a 17% improvement over the manual method. The application of the developed method to radiography of dental implants provides an automatic noise robust registration with high accuracy in almost real time.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.9-14
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• 2018

The vision system is a device for acquiring images and analyzing and discriminating inspection areas. Demand for use in the automation process has increased, and the introduction of a vision-based inspection system has emerged as a very important issue. These vision systems are used for everyday life and used as inspection equipment in production processes. Image processing technology is actively being studied. However, there is little research on the area definition for extracting objects such as character recognition or semiconductor packages. In this paper, define a region of interest and perform edge extraction to prevent the user from judging noise as an edge. We propose a noise-robust alignment correction model that can extract the edge of a region to be inspected using the distribution of edges in a specific region even if noise exists in the image. Through the proposed model, it is expected that the product production efficiency will be improved if it is applied to production field such as character recognition of tire or inspection of semiconductor packages.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.75-80
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• 2021

This paper relates with the Hybrid-DSE-MMA (Hybrid-Dithered Signed Error-MMA) that is possible to improving the equalization performance by using the adaptive modulus and adaptive stepsize in DSE-MMA adaptive equalizer. The DSE-MMA possible to improve the robustness performance to external noise of SE-MMA by using the sign after adding the dither signal for get the error signal in order to update the tap coefficient. But it has a drawback of performance degradation in convergence speed and residual isi by using the fixed modulus and fixed stepsize. In this paper, it was confirmed that this equalization performance degradation was improved by applying the adaptive modulus and stepsize in DSE-MMA propotional to the output power of equalizer by computer simulation. In order to compare the improved equalization performance to currently DSE-MMA, the recovered signal constellation that is the output of the equalizer, residual isi, Maximum Distortion, MSE and the SER were used as a performance index. As a result of computer simulation, the Hybrid-DSE-MMA improve the equalization performance in every index, but gives slower convergence speed compared to DSE-MMA.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2149-2151
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• 2003

본 논문에서는 마이컴(PIC16C74)과 Tabu 탐색법 및 지능기법(퍼지 및 신경회로망)을 이용하여 고정밀 제어 및 강인한 제어 성능을 가지는 초소형 DC 모터용 지능형 제어기를 개발하였다. 이를 위해 마이컴(PIC16C74)를 이용한 지능형 제어 알고리즘을 개발하고, 초소형 DC 모터용 드라이브 회로 설계 및 제작하였다. 개발한 초소형 DC 모터 지능형 제어기는 디지털 자동 용접캐리지에 적용할 예정이며, 다른 응용 분야로써는 자동배수장치, 반도체 분야, 산업용 로봇 분야 및 조립자동화 시스템 분야 등에 사용되는 구동모터에 적용함으로서 정밀도와 외부의 잡음에 대한 영향을 경감시켜 안정성과 효율향상 및 에너지절약이 가능할 것이다.

• The Journal of the Acoustical Society of Korea
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• v.20 no.1
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• pp.36-42
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• 2001

This paper propose new sound localization algorithm that detects the sound source bearing in a closed office environment using two microphone array. The proposed Subband CPSP (Cross Power Spectrum Phase) algorithm is a development of previously Down CPSP method using subband approach. It first split the received microphone signals into subbands and then calculates subband CPSP which result in possible source bearings. This type of algorithm, Subband CPSP, can provide more robust and reliable sound localization system because it limits the effects of environmental noise within each subband. To verify the performance of the proposed Subband CPSP algorithm, a real time simulation was conducted and it was compared with previous CPSP method. From the simulation results, the proposed Subband CPSP is superior to previous CPSP algorithm more than 5％ average accuracy for sound source detection.