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

• 대한전자공학회논문지SP
• /
• 제38권1호
• /
• pp.19-32
• /
• 2001

본 논문에서는 영상의 밝기 값을 마치 3차원 지형과 같은 개념으로 간주하여 여기에 물이 흐르는 개념을 적용하여 국부 적응 (locally adaptive) thresholding 방법을 제안하였다. 문자를 추출해내기 위해 제안한 방법에서는 지형 표면에 물을 붓는 과정을 수행하였다. 물은 지형의 낮은 곳으로 흐르게 되어 계곡 (valley)에 쌓인다. 이때 문자와 배경으로 구성된 문서영상에서 쌓인 물의 양을 기준으로 두 개의 영역을 구분을 하였다. 제안한 water flow model의 개념을 적용한 threholding 방법은 국부 적응 thresholding의 특성을 나타낸다. 합성 영상과 실제 영상을 이용하여 전산 모의 실험을 수행함으로써 제안한 방법이 문서 영상을 효과적으로 이진화할 수 있음을 보였다.

• 한국가정과학회지
• /
• 제1권2호
• /
• pp.113-118
• /
• 1998

Clothing shape is principally described in seven factors that are composed of clothing design, clothing material, clothing size, pattern design, sewing method and body motion etc.. The aims of this study was to measurement out-line space-shape variation of clothing fitness with somato type by using the image processing. The subjects for direct anthropometric measurements were 248 female college students aged from 19 to 22. The data were statistically analyzed by principal analysis and cluster analysis. The results were obtained three somato type. Also I made skirts in order to analyzed to the out-line space-shape variation of clothing fitness with body. The effect of somato type on the shape of flare skirts was determined by the out-line space-shape variation of clothing fitness with body. The out-line space-shape variation of clothing fitness with body was observed between the node number and amplitudes of clothing wave form and node number was determined at the maxim of space-shape amplitude, and the space-shape amplitudes have related with aspect ratio of cross-sectional shape. Results for flare skirts show changes in amplitude and mean with fabrics, somato type. therefore gray-level histogram are correlated with changes out-line space-shape, differences in drape spacing and related fabric properties and their somato type. (Korean J Human Ecology 1(2):113∼110 1998)

• 한국통신학회논문지
• /
• 제28권3C호
• /
• pp.327-335
• /
• 2003

Cellular Automata는 자연계의 현상 현상이 국부적인 관계에 의해 완전히 표현될 수 있는 이상적인 동적 시스템이다. 본 논문에서는 Cellular Automata의 특성을 가지는 Potts Automata를 이용한 잡음 제거 및 에지 추출 알고리즘을 제안한다. 본 방법은 대상영상에 대한 특징을 그대로 보존하면서 천이규칙에 따라 국부적으로 밝기값의 차이를 증가 및 감소시킨다. 이러한 Automata는 순차적이고 병렬적인 움직임을 가지고 Lyapunov 함수를 만족한다. 제안한 천이규칙은 랜덤잡음을 가진 대상영상에 대해 빠른 수련속도를 가지고 안정적인 결과를 나타낸다. 실험을 통해 본 방법의 유효성을 확인한다.

• 전자공학회논문지B
• /
• 제32B권11호
• /
• pp.1445-1454
• /
• 1995

In this study, we have developed a prototype of the automatic defects detection system for capsule inspection using the computer vision techniques. The subjects for inspection are empty hard capsules of various sizes which are made of gelatine. To inspect both sides of a capsule, 2-stage recognition is performed. Features we have used are various lengths of a capsule, area, linearity, symmetricity, head curvature and so on. Decision making is performed based on average value which is computed from 20 good capsules in training and permission bounds in factories. Most of time-consuming process for feature extraction is computed by hardware to meet the inspection speed of more than 20 capsules/sec. The main logic for control and arithmetic computation is implemented using EPLD for the sake of easy change of design and reduction in time for developement. As a result of experiment, defects on size or contour of binary images are detected over 95%. Because of dead zone in imaging system, detection ratio of defects on surface, such as bad joint, chip, speck, etc, is lower than the former case. In this case, detection ratio is 50-85%. Defects such as collet pinch and mashed cap/body seldom appear in binary image, and detection ratio is very low. So we have to process the gray-level image directly in partial region.

• Journal of Electrical Engineering and Technology
• /
• 제13권3호
• /
• pp.1383-1391
• /
• 2018

A new nonlinear filtering algorithm for effectively denoising images corrupted by the random-valued impulse noise, called dual sliding statistics switching median (DSSSM) filter is presented in this paper. The proposed DSSSM filter is made up of two subunits; i.e. Impulse noise detection and noise filtering. Initially, the impulse noise detection stage of DSSSM algorithm begins by processing the statistics of a localized detection window in sorted order and non-sorted order, simultaneously. Next, the median of absolute difference (MAD) obtained from both sorted statistics and non-sorted statistics will be further processed in order to classify any possible noise pixels. Subsequently, the filtering stage will replace the detected noise pixels with the estimated median value of the surrounding pixels. In addition, fuzzy based local information is used in the filtering stage to help the filter preserves the edges and details. Extensive simulations results conducted on gray scale images indicate that the DSSSM filter performs significantly better than a number of well-known impulse noise filters existing in literature in terms of noise suppression and detail preservation; with as much as 30% impulse noise corruption rate. Finally, this DSSSM filter is algorithmically simple and suitable to be implemented for electronic imaging products.

• 한국멀티미디어학회논문지
• /
• 제11권12호
• /
• pp.1635-1648
• /
• 2008

The extraction of important features in cancer cell image analysis is a key process in grading renal cell carcinoma. In this study, we applied three-dimensional (3D) texture feature extraction methods to cell nuclei images and evaluated the validity of them for computerized cell nuclei grading. Individual images of 2,423 cell nuclei were extracted from 80 renal cell carcinomas (RCCs) using confocal laser scanning microscopy (CLSM). First, we applied the 3D texture mapping method to render the volume of entire tissue sections. Then, we determined the chromatin texture quantitatively by calculating 3D gray-level co-occurrence matrices (3D GLCM) and 3D run length matrices (3D GLRLM). Finally, to demonstrate the suitability of 3D texture features for grading, we performed a discriminant analysis. In addition, we conducted a principal component analysis to obtain optimized texture features. Automatic grading of cell nuclei using 3D texture features had an accuracy of 78.30%. Combining 3D textural and 3D morphological features improved the accuracy to 82.19%. As a comparative study, we also performed a stepwise feature selection. Using the 4 optimized features, we could obtain more improved accuracy of 84.32%. Three dimensional texture features have potential for use as fundamental elements in developing a new nuclear grading system with accurate diagnosis and predicting prognosis.

• 정보처리학회논문지:소프트웨어 및 데이터공학
• /
• 제2권8호
• /
• pp.579-588
• /
• 2013

본 논문에서는 화재 비디오 영상의 저작권 보호를 위해 효과적인 워터마킹 기법을 제안한다. 제안하는 워터마킹 기법은 명암도 동시발생 행렬과 퍼지 클러스터링 알고리즘을 이용하여 화재의 색상과 텍스처의 특징을 효율적으로 이용한다. 명암도 동시발생 행렬은 각 후보 화재 영상의 블록에 대한 에너지와 동질성을 계산하여 텍스처 데이터 셋을 만드는데 사용하며, 퍼지 클러스터링은 화재 비디오 영상의 색상 분할과 워터마커 삽입을 위한 텍스처 블록을 결정하기 위해 사용된다. 선택된 텍스처 블록은 이산 웨이블릿 변환을 통해 네 가지 서브밴드 (LL, LH, HL, HH)를 가지는 1차 레벨 웨이블릿 구조로 분해되고, 워터마커는 사람의 시각에 영향을 주지 않는 LH 영역에 삽입된다. 모의실험결과, 제안한 워터마킹 기법은 약 48 데시벨의 높은 첨부 신호 대 잡음 비와 1.6-2.0의 낮은 M-특이치 분해 값을 보였다. 또한, 제안한 워터마킹 기법은 노이즈 첨가, 필터링, 크로핑, JPEG 압축과 같은 영상처리 공격에서도 기존 이미지 워터마킹 알고리즘보다 정규화된 상관 값에서 높은 성능을 보였다.

• 대한전자공학회논문지SP
• /
• 제44권3호
• /
• pp.80-87
• /
• 2007

국부 통계치에 근거한 서양금석문 영상향상 기법을 고안한다. 영상데이터는 배경과 정보의 두 영역으로 구분한다. 통계 및 함수적 분석을 통해 서양금석문 영상 대부분이 가우스 회색도분포임을 규명하고 분포 및 영역특성을 고려한 모델을 구현한다. 모델을 대상으로 국부정규화처리 알고리즘을 수식화하고 파라미터를 추출하며 이동창에서의 기능과 특성을 논의한다. 파라미터와 이동창의 크기를 조정하여 화소 회색도의 공간 분포를 변형하고 영역을 선별한다. 이 때 국부통계치는 알고리즘을 실현하는 유용한 근거로 활용된다. 알고리즘 적용에 의해 영역의 잡음과 불규칙한 분포 상태가 평활되는 동시에 영역 사이의 회색도 격차를 증대시켜 영상을 향상한다. 실험결과는 제안된 방식이 기존의 영상향상 기법보다 우수한 효과가 있음을 보여준다.

• 대한기계학회논문집B
• /
• 제23권3호
• /
• pp.398-407
• /
• 1999

In the present image processing technique, the concept of the gradient indicator(GI) has been introduced to find out the depth-of-field in sizing large particles ranging from $30{\mu}m$ to $30{\mu}m$ where using of the concept of the normalized contrast value(VC) is not appropriate. The gradient indicator is defined as the ratio of the local value to the maximum possible value of the gray-level gradient in an image frame. The gradient indicator decreases with the increases of the particle size and the distance from the exact focal plane. A particle is considered to be in focus when the value of the gradient indicator at its image boundary stays above a critical value. This critical gradient indicator($GI_{critical}$) is defined as the maximum gradient indicator($GI_{max}$) subtracted by a constant ${\Delta}GI$ which is to account for the particle-size effect. In the present ca.so, the value of ${\Delta}GI$ was set to 0.28 to keep the standard deviation of the measured particles mostly within 0.1. It was also confirmed that, to find the depth-of-field for small particles(${\leq}30{\mu}m$) with the same measurement accuracy, tho concept of the critical normalized contrast($VC_{critical}$) is applicable with 85% of the maximum normalized contrast value($VC_{max}$). Finally, the depth-of-field was checked for the size range between $10{\mu}m$ and $300{\mu}m$ when the both in-focus criteria ($GI_{critical}$ and $VC_{critical}$) were adopted. The change of the depth-of-field with the particle size shows good linearity in both the VC-applicable and the GI-applicable ranges with a reasonable accuracy.