• 한국멀티미디어학회논문지
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• 제14권12호
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• pp.1544-1548
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• 2011

A process of choosing a subset of original features, so called feature selection, is considered as a crucial preprocessing step to image processing applications. There are already large pools of techniques developed for machine learning and data mining fields. In this paper, basically two methods, non-feature selection and feature selection, are investigated to compare their predictive effectiveness of classification. Color co-occurrence feature is used for defining image features. Standard Sequential Forward Selection algorithm are used for feature selection to identify relevant features and redundancy among relevant features. Four color spaces, RGB, YCbCr, HSV, and Gaussian space are considered for computing color co-occurrence features. Gray-level image feature is also considered for the performance comparison reasons. The experimental results are presented.

• 한국멀티미디어학회논문지
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• 제7권12호
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• pp.1639-1649
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• 2004

In this paper, a method for detection of forged signatures based on spectral analysis of directional gradient density function and a weighted fuzzy classifier is proposed. The well defined outline of an incoming signature image is extracted in a preprocessing stage which includes noise reduction, automatic thresholding, image restoration and erosion process. The directional gradient density function derived from extracted signature outline is highly related to the overall shape of signature image, and thus its frequency spectrum is used as a feature set. With this spectral feature set, having a property to be invariant in size, shift, and rotation, a weighted fuzzy classifier is evaluated for the verification of freehand and random forgeries. Experiments show that less than 5% averaged error rate can be achieved on a database of 500 signature samples.

• 통합자연과학논문집
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• 제12권4호
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• pp.105-115
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• 2019

In this paper, a prediction system is proposed to control the brightness of smart street lamps by predicting the moving path through the reduction of consumption power and information of pedestrian's past moving direction while meeting the function of existing smart street lamps. The brightness of smart street lamps is adjusted by utilizing the walk tracking vector and soft hand-off characteristics obtained through the motion sensing sensor of smart street lamps. In addition, the motion vector is used to analyze and predict the pedestrian path, and the GPU is used for high-speed computation. Pedestrians were detected using adaptive Gaussian mixing, weighted difference imaging, and motion vectors, and motions of pedestrians were analyzed using the extracted motion vectors. The preprocessing process using linear interpolation is performed to improve the performance of the proposed prediction system. Fuzzy prediction system and neural network prediction system are designed in parallel to improve efficiency and rough set is used for error correction.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2192-2197
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• 2005

This paper describes how to diagnose SBR plant equipment using time-series data mining. It shows the equipment diagnostics based upon vibration signals that are acquired from each device for process control. Data transform techniques including two data preprocessing skills and data mining methods were employed in the data analysis. The proposed method is not only suitable for SBR equipment, but is also suitable for other industrial devices. The experimental results performed on a lab-scale SBR plant show a good equipment-management performance.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1689-1694
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• 2005

Face detection plays an important role in face recognition, video surveillance, and human computer interface. In this paper, we present a face detection system using eye detection with progressive thresholding from a digital camera. The face candidate is detected by using skin color segmentation in the YCbCr color space. The face candidates are verified by detecting the eyes that is located by iterative thresholding and correlation coefficients. Preprocessing includes histogram equalization, log transformation, and gray-scale morphology for the emphasized eyes image. The distance of the eye candidate points generated by the progressive increasing threshold value is employed to extract the facial region. The process of the face detection is repeated by using the increasing threshold value. Experimental results show that more enhanced face detection in real time.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.101.4-101
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• 2001

Evolutionary algorithm has been receiving a remarkable attention due to the model-free and population-based parallel search attributes and much successful results are coming out. However, there are some problems in most of the evolutionary algorithms. The critical one is that it takes much time or large generations to search the global optimum in case of the objective function with multimodality. Another problem is that it usually cannot search all the local optima because it pays great attention to the search of the global optimum. In addition, if the objective function has several global optima, it may be very difficult to search all the global optima due to the global characteristics of the selection methods. To cope with these problems, at first we propose a preprocessing process, grid-filtering algorithm(GFA), and propose a new distributed evolutionary ...

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.32.2-32
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• 2002

In this paper, an efficient FFT-based fault detection algorithm is proposed. In our proposed method, fault detection is accomplished by process similar to the conventional FFT-based fault detection. However, the proposed technique adopts fast algorithms for preprocessing, where the conventional operation such as averaging is replaced with recursive average operation that outperforms the former in computational cost. And, the proposed approach utilizes the feature vector with the small dimension, which is extracted from spectral components of the lower and upper sidebands around the fundamental frequency. The mean absolute difference (MAD) criterion is used to finally determine whether motor...

• 제어로봇시스템학회논문지
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• 제10권6호
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• pp.494-500
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• 2004

This paper presents a machine vision system, which inspects the measurement of the ALC block on a real-time basis in the production process. The automatic measurement system was established with a CCD camera, an image grabber, and a personal computer without using assembled measurement equipment. Images obtained by this system was processed by an algorithm, specially designed for an enhanced measurement accuracy. For the realization of the proposed algorithm, a preprocessing method that can be applied to overcome uneven lighting environment, boundary decision method, unit length decision method in uneven condition with rocking objects, and a projection of region using pixel summation are developed. From our experimental results, we could find that the required measurement accuracy specification is sufficiently satisfied by using the proposed method.

• 천문학논총
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• 제20권1호
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• pp.97-107
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• 2005

We developed a data reduction program (RX) to process BOES data automatically. It processes a whole set of data taken during one night automatically - preprocessing, extraction to one-dimensional spectra and wavelength calibration. The execution is very fast and the performance looks pretty good. We described the performance of this program, comparing its procedure with that of IRAF. RX does not have functions for continuum normalization yet. We will develop those functions in the next works.

• 한국정보통신학회논문지
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• 제9권4호
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• pp.890-895
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• 2005

동적(온라인) 서명인증시스템은 내부 처리 과정에서는 불필요한 점들을 제거하는 전처리과정, 서명의 변화폭을 줄여주고 서명자의 고유한 특징 정보를 추출하는 특징추출과정, 두 서명의 특징벡터를 비교하여 유사도를 계산하는 비교과정, 보안수준에 따른 인증 여부를 결정하는 판단과정으로 구성되며, 사용자 관점에서의 화면 구성은 서명을 입력받아 기준서명과 보안수준 값을 만들어 주는 등록화면과 권한 부여를 위하여 진서명인지 모조서명인지를 판단하는 인증화면으로 나누어진다. 본 논문에서는 동적 서명인증시스템의 처리 속도, 서명의 특징벡터의 추출방법과 비교 알고리즘, 사용자 인터페이스 등과 실제 환경에서의 설계 및 구현에 대한 연구이다.