• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.444-449
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• 1996

The semiconductor, which is precision product, requires many inspection processes. The surface conditions of the semiconductor chip affect on the functions of the semiconductors. The defects of the chip surface are cracks or voids. As general inspection method requires many inspection procedure, the inspection system which searches immediately and precisely the defects of the semiconductor chip surface is required. We suggest the detection algorithm for inspecting the surface defects of the semiconductor surface. The proposed algorithm first regards the semiconductor surface as random texture and point spread function, and secondly presents the character of texture by linear estimation theorem. This paper assumes that the gray level of each pixel of an image is estimated from a weighted sum of gray levels of its neighbor pixels by linear estimation theorem. The weight coefficients are determined so that the mean square error is minimized. The obtained estimation window(two-dimensional estimation window) characterizes the surface texture of semiconductor and is used to discriminate the defects of semiconductor surface.

• 한국음향학회지
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• 제30권2호
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• pp.100-106
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• 2011

음원의 디지털화가 진행되면서 음악 데이터베이스가 방대해지고 있다. 따라서, 음악 데이터를 보다 효과적으로 관리하기 위해 음악의 특성에 따라 장르별로 자동 분류해주는 시스템이 필요하다. 기존 장르 분류 시스템은 대부분 Mel-Frequency Cepstral Coefficient (MFCC)를 특징 벡터로 이용하고 있다. 본 논문에서는 Auditory Filter Bank를 이용한 Decorrelated Filter Bank (DFB)와 Octave-based Spectral Contrast (OSC)에 texture window를 적용하여 특징을 추출한 후, Support Vector Machine (SVM)을 이용하여 장르 분류를 시도하였다. 기존의 Marsyas 장르 분류 시스템과 비교한 결과 DFB와 OSC로 복합적인 특징 벡터를 구성하면 더 적은 차수의 특징벡터를 사용함에도 4.2 %의 향상된 분류 성공률을 얻을 수 있었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.2059-2064
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• 2004

Texture analysis is an important role for automatic visual insfection. This paper presents an application of wavelet extension and Gray level co-occurrence matrix (GLCM) for detection of defect encountered in textured images. Texture characteristic in low quality images is not to easy task to perform caused by noise, low frequency and small dimension. In order to solve this problem, we have developed a procedure called wavelet image extension. Wavelet extension procedure is used to determine the frequency bands carrying the most information about the texture by decomposing images into multiple frequency bands and to form an image approximation with higher resolution. Thus, wavelet extension procedure offers the ability to robust feature extraction in images. Then the features are extracted from the co-occurrence matrices computed from the sub-bands which performed by partitioning the texture image into sub-window. In the detection part, Mahalanobis distance classifier is used to decide whether the test image is defective or non defective.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2001년도 추계종합학술대회
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• pp.363-366
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• 2001

현재 육안에 의한 피혁의 등급 판정 과정은 장시간 시 피로에 의한 일관성 결여로 인해 판정 결과에 대한 신뢰성을 주지 못한다. 따라서 피혁의 품질을 결정하기 위한 객관적인 지표와 이를 기준으로 등급 판정 과정의 자동화가 필요하다. 본 논문에서 적용된 피혁 자동 선별 시스템은 피혁에 대한 정보를 취득하는 과정과 이들 정보로부터 등급을 판정하는 과정으로 구성된다. 피혁의 품질은 조밀도와 결함의 종류 및 분포도와 같은 피혁 정보에 의해 결정된다. 본 논문에서는 디지털 카메라에 의해 획득된 흑백 영상으로부터 피혁의 조밀도 및 결함에 대한 정보를 추출하는 알고리즘을 제안한다. 조밀도에 대한 정보는 원 영상을 주파수 영역으로 변환한 후 나타나는 퓨리에 스펙트럼 분포의 특징 값들에 의해서 추출된다. 그리고 결함에 대한 정보는 전처리 과정을 거친 영상으로부터 경계선 검출 후 검색 윈도우를 사용하여 윈도우에 해당하는 픽셀들의 통계적 수치에 의해서 검출된다. 피혁 전체에 대한 정보들은 피혁의 등급을 판정하는 지표로 사용되며 실제 머신 비젼 시스템에 적용된다.

• 한국초전도ㆍ저온공학회논문지
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• 제5권3호
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• pp.11-14
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• 2003

The detailed conditions of dc-sputtering for depositions of yttria-stabilized ZrO$_2$ (YSZ) films were investigated, while the films were grown on the CeO$_2$ template layers on biaxially textured Ni-tapes. The window of oxygen pressures for proper growth of YSZ films, which was dependent on sputtering powers, was determined by sufficient oxidations of the YSZ films and the de-oxidation of the target surface, which was required for rapid sputtering. The window turned out to be fairly wide under certain values of argon pressure. When the sputtering power was raised, the deposition rate increased without narrowing the window. The fabricated YSZ films showed good texture qualities and surface morphologies.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.698-701
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• 2005

This paper examines that is extracted certain information in forest areas within high resolution imagery based on wavelet transformation. First of all, study areas are selected one more species distributed spots refer to forest type map. Next, study area is cut 256 x 256 pixels size because of image processing problem in large volume data. Prior to wavelet transformation, five texture parameters (contrast, dissimilarity, entropy, homogeneity, Angular Second Moment (ASM≫ calculated by using Gray Level Co-occurrence Matrix (GLCM). Five texture images are set that shifting window size is 3x3, distance .is 1 pixel, and angle is 45 degrees used. Wavelet function is selected Daubechies 4 wavelet basis functions. Result is summarized 3 points; First, Wavelet transformation images derived from contrast, dissimilarity (texture parameters) have on effect on edge elements detection and will have probability used forest road detection. Second, Wavelet fusion images derived from texture parameters and original image can apply to forest area classification because of clustering in Homogeneous forest type structure. Third, for grading evaluation in forest fire damaged area, if data fusion of established classification method, GLCM texture extraction concept and wavelet transformation technique effectively applied forest areas (also other areas), will obtain high accuracy result.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.799-802
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• 2000

There are many methods that extract the depth information based on the blurring ratio for object point in DFD(Depth from Defocus). However, it is often difficult to measure the depth of the object in two-dimensional images that was affected by various elements such as edges, textures, and etc. To solve the problem, new DFD method employing the texture classification with a neural network is proposed. This method extracts the feature of texture from an evaluation window in an image and classifies the texture class. Finally, It allocates the correspondent value for the blurring ratio. The experimental result shows that the method gives more accurate than the previous methods.

• 대한원격탐사학회지
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• 제25권3호
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• pp.295-309
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• 2009

In this study, an iterative maximum a posteriori (MAP) approach using a Bayesian model of Markovrandom field (MRF) was proposed for despeckling images that contains speckle. Image process is assumed to combine the random fields associated with the observed intensity process and the image texture process respectively. The objective measure for determining the optimal restoration of this "double compound stochastic" image process is based on Bayes' theorem, and the MAP estimation employs the Point-Jacobian iteration to obtain the optimal solution. In the proposed algorithm, MRF is used to quantify the spatial interaction probabilistically, that is, to provide a type of prior information on the image texture and the neighbor window of any size is defined for contextual information on a local region. However, the window of a certain size would result in using wrong information for the estimation from adjacent regions with different characteristics at the pixels close to or on boundary. To overcome this problem, the new method is designed to use less information from more distant neighbors as the pixel is closer to boundary. It can reduce the possibility to involve the pixel values of adjacent region with different characteristics. The proximity to boundary is estimated using a non-uniformity measurement based on standard deviation of local region. The new scheme has been extensively evaluated using simulation data, and the experimental results show a considerable improvement in despeckling the images that contain speckle.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2012년도 제43회 하계 정기 학술대회 초록집
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• pp.304-304
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• 2012

III-V 화합물 태양전지는 실리콘 등 다른 태양전지에 비해 1sun상 30% 이상의 고효율을 갖고 있고 direct bandgap과 높은 이동도 등의 물질특성과 3족과 5족의 비율 조절로 같은 결정구조에서 에너지 bandgap이 다른 물질들을 만들기에 용이하여 태양전지 스펙트럼의 넓은 영역을 흡수할 수 있는 장점이 있다. 그러나 셀 자체의 물질이 실리콘에 비하여 고가여서 고성능이 요구되는 우주 인공위성 등에 적용이 되었지만, 2000년대 이후로 집광에 적용 가능한 태양전지의 연구를 거듭하여 2005년부터는 값싼 프레넬 렌즈를 이용하여 1 sun에 비해 500배 해당하는 빛을 셀에 집광하여 보다 효율을 증가시킴으로써 지상발전용에도 적용 가능한 셀을 형성하게 되었다. 더불어 태양전지의 효율을 증가시키기 위한 다양한 구조적 변화의 시도도 많이 이루어지고 있다. 최근 실리콘 태양전지의 표면에 texture 구조를 주어 높은 흡수율과 낮은 반사율을 갖게 함으로써 효율을 증가시키는 사례가 많아지고, III-V 화합물 태양전지도 texturing에 의해 증가된 효율을 발표한바 있다. 본 연구에서는 III-V 화합물 InGaP 태양전지의 window층으로 사용되는 InAlP 층에 Metal-assisted chemical etching (mac etching) 방법으로 texture 구조를 형성하여 etching 시간에 따른 InAlP층의 표면 변화와 반사율의 변화를 분석하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권1호
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• pp.224-241
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• 2015

Multiview plus depth (MVD) videos are widely used in free-viewpoint TV systems. The best-known technique to determine depth information is based on stereo vision. In this paper, we propose a novel local stereo matching algorithm which is radiometric invariant. The key idea is to use a combined matching cost of intensity and gradient based similarity measure. In addition, we realize an adaptive cost aggregation scheme by constructing an adaptive support window for each pixel, which can solve the boundary and low texture problems. In the disparity refinement process, we propose a four-step post-processing technique to handle outliers and occlusions. Moreover, we conduct stereo reconstruction tests to verify the performance of the algorithm more intuitively. Experimental results show that the proposed method is effective and robust against local radiometric distortion. It has an average error of 5.93% on the Middlebury benchmark and is compatible to the state-of-art local methods.