• 음성과학
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• 제4권2호
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• pp.55-68
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• 1998

In this paper, a novel method of noise reduction of speech based on a complex adaptive noise canceler and method of optimal feature extraction are proposed. This complex adaptive noise canceler needs simply the noise detection, and LMS algorithm used to calculate the adaptive filter coefficient. The method of optimal feature extraction requires the variance of noise. The experimental results have shown that the proposed method effectively reduced noise in noisy speech. Optimal feature extraction has shown similar characteristics in noise-free speech.

• 한국전자파학회논문지
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• 제14권8호
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• pp.823-829
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• 2003

고주파용 마이크로스트립 선로의 모델링에 필수적인 인덕턴스의 빠른 추출을 위해서 고속화 알고리즘(fast mutilpole method)과 결합된 적응 PEEC 격자분할법(adaptive PEEC grid refinement algorithm)을 제안하였다. 격자의 세분화는 마이크로스트립 선로의 구조와 사용주파수에 따른 전류분포에 적합하도록 이루어졌는데, 이 적응 격자는 주로 전류분포가 높은 영역에서 더 세분화된다. 이 기법을 이용하여 마이크로스트립 선로의 인덕턴스를 구하였고, 계산결과는 빠르게 수렴하여 계산시간과 격자 수를 줄이는데 효율적임을 보였다.

• ETRI Journal
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• 제37권5호
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• pp.1023-1031
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• 2015

In infrared (IR) images, near targets have a transient distribution at the boundary region, as opposed to a steady one at the inner region. Based on this fact, this paper proposes a novel IR target extraction method that uses both a weighted information entropy (WIE) and an adaptive opening filter to extract near finely shaped targets in IR images. Firstly, the boundary region of a target is detected using a local variance WIE of an original image. Next, a coarse target region is estimated via a labeling process used on the boundary region of the target. From the estimated coarse target region, a fine target shape is extracted by means of an opening filter having an adaptive structure element. The size of the structure element is decided in accordance with the width information of the target boundary and mean WIE values of windows of varying size. Our experimental results show that the proposed method obtains a better extraction performance than existing algorithms.

• 한국통신학회논문지
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• 제16권12호
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• pp.1249-1265
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• 1991

본 논문에서는 texture 영상 분할을 위한 새로운 고속 적응 texture 특징 추출 방법을 제안하였다. 먼저 기존의 통계적 texture 특징 추출 방법에 대하여 설명하였으며, SGLDM을 구하는 방법과 이것을 이용하여 추출할 수 있는 textrue 특징들에 관하여 기술하였다. 그리고 고속으로 특징을 추출하기 위한 반복 계산식을 각 특징에 대하여 유도하였으며 반복 계산식으로 이용하여 고속 적응 texture 특징을 방법에 대하여 설명하였다. 마지막으로 제안된 방법의 성능을 평가하기 위하여 인공적으로 합성한 texture 영상에 대하여 컴퓨터 시뮬레이션을 수행하였다. 그 결과 기존의 방법과 비교해서 영역의 경계부분에서 비교적 정확한 특징값을 추출할 수 있음을 알 수 있었다.

• 대한원격탐사학회지
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• 제17권4호
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• pp.319-334
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• 2001

Extracting primitives from imagery plays an important task in visual information processing since the primitives provide useful information about characteristics of the objects and patterns. The human visual system utilizes features without difficulty for image interpretation, scene analysis and object recognition. However, to extract and to analyze feature are difficult processing. The ultimate goal of digital image processing is to extract information and reconstruct objects automatically. The objective of this study is to develop robust method to achieve the goal of the image processing. In this study, an adaptive strategy was developed by implementing Gabor filters in order to extract feature information and to segment images. The Gabor filters are conceived as hypothetical structures of the retinal receptive fields in human vision system. Therefore, to develop a method which resembles the performance of human visual perception is possible using the Gabor filters. A method to compute appropriate parameters of the Gabor filters without human visual inspection is proposed. The entire framework is based on the theory of human visual perception. Digital images were used to evaluate the performance of the proposed strategy. The results show that the proposed adaptive approach improves performance of the Gabor filters for feature extraction and segmentation.

• 한국전자파학회논문지
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• 제14권1호
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• pp.27-32
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• 2003

본 논문에서는 수 만개 이상의 미지수를 필요로 하는 복잡한 3차원 구조에서의 정전용량 추출을 위한 고속화 알고리즘(Fast mutilpole method)과 결합한 효과적인 적응 삼각요소 분할법(Adaptive triangular mesh refinement algorithm)을 제안하였다. 적응 삼각요소 분할법은 3차원 물체의 표면을 초기요소로 분할하여 전하의 분포를 구하고, 전하밀도가 높은 영역에서의 요소세분화를 수행하여 이루어진다. 제안된 방법을 이용하여 많은 미지수를 필요로 하는 68-pin cerquad package구조에서의 정전용량을 추출하였다.

• 한국정보통신학회논문지
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• 제7권8호
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• pp.1802-1808
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• 2003

본 논문은 자동 보행자 추적 시스템에 필요한 배경 이미지를 추출하는 방법과 추출되어진 배경 이미지를 이용하여 보행자를 탐지하고 적응적 신경망을 이용하여 보행자의 이동 궤적을 추적하는 시스템을 구현하였다. 본 논문은 고스트(ghost) 현상을 극복하기 위하여 모자이크 배경 이미지 추출 법으로 배경 이미지를 추출하였으며, 보행자의 탐지에 차영상 분석법을 기반으로 하여 보행자를 탐지하였다. ART2 네트워크는 프레임에 존재하는 이동 물체의 중심점을 탐지할 수 있다. 그리고, 이전 프레임에서 탐지되어진 물체의 정보를 이용하여 물체의 이동궤적을 추적할 수 있다. 제안하는 방법으로 실험한 결과 비강체(non­rigid)형태 운동을 하는 보행자를 탐지하고 그 궤적 추적에 대한 실시간 시스템 구성의 가능성에 대하여 알 수 있었다.

• Current Optics and Photonics
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• 제7권4호
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• pp.387-397
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• 2023

Tooth surface shape error is an important parameter in gear accuracy evaluation. When tooth surface shape error is measured by laser interferometry, the gear interferogram is highly distorted and the gray level distribution is not uniform. Therefore, it is important for gear interferometry to extract the foreground region from the gear interference fringe image directly and accurately. This paper presents an approach for foreground extraction in gear interference images by leveraging the sinusoidal variation characteristics shown by the interference fringes. A gray level mask with an adaptive threshold is established to capture the relevant features, while a local variance evaluation function is employed to analyze the fluctuation state of the interference image and derive a repair mask. By combining these masks, the foreground region is directly extracted. Comparative evaluations using qualitative and quantitative assessment methods are performed to compare the proposed algorithm with both reference results and traditional approaches. The experimental findings reveal a remarkable degree of matching between the algorithm and the reference results. As a result, this method shows great potential for widespread application in the foreground extraction of gear interference images.

• IEIE Transactions on Smart Processing and Computing
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• 제5권1호
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• pp.49-54
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• 2016

Regarding global and local factors of a set of features, a given single image or multiple images is a common approach in image processing. This paper introduces an application of an adaptive version of non-local filter whose original version searches non-local similarity for removing noise. Since most images involve texture partner in both foreground and background, extraction of signified regions with texture is a challenging task. Aiming to the detection of visual attention regions for images with texture, we present the contrast analysis of image patches located in a whole image but not nearby with assistance of the adaptive filter for estimation of non-local divergence. The method allows extraction of signified regions with texture of images of wild life. Experimental results for a benchmark demonstrate the ability of the proposed method to deal with the mentioned challenge.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.2331-2334
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• 2003

Generally, skin color information has been widely used at the face region extraction step of the face region recognition process. But many experimental results show that they are very sensitive to the given threshold range which is used to extract the face regions at the input image. In this paper, we propose a face region extraction algorithm based on an adaptive range decision for skin color. First we extract the pixels which are regarded as the candidate skin color pixels by using the given range for skin color extraction. Then, the ratio between the total pixels and the extracted pixels is calculated. According to the ratio, we adaptively decide the range of the skin color and extract face region. From the experiment results for the various images, the proposed algorithm shows more accurate results than the conventional algorithm.