• Journal of the Institute of Convergence Signal Processing
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• v.8 no.4
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• pp.249-254
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• 2007

This paper describes a technique for detecting the boundary of the optic disk in digital image of the retina using inward and outward curve evolution. Optic disk boundary offers medical information about glaucoma progresses. For accurate boundary detection, image inpainting based on PDE removes blood vessels crossing the optic disk. For removing noises and preserving boundary of optic disk in image inpainting process, the anisotropic diffusion filtering is developed. After pre-processing, the optic disk boundary is determined using inward and outward curve evolution. Experimental results show that blurring effect of original region and optic disk boundary is reduced considerably. By the proposed method, we can detect correct disk boundary compare to conventional method.

• Proceedings of KOSOMES biannual meeting
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• 2005.11a
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• pp.197-202
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• 2005

Generally, a semiconductor chip measured with a few micro units is captured by line scan camera for higher inspection accuracy. However, the faulty inspection requires an exact boundary detection algorithm because it is very sensitive to scan speed and lighting conditions. In this paper we propose boundary detection using subpixel edge detection method in order to increase the accuracy of bump faulty detection on chips. The bump edge is detected by first derivative to four directions from bump center point and the exact edge positions are searched by the subpixel method. Also, the exact bump boundary to calculate the actual bump size is computed by LSM(Least Squares Method) to minimize errors since the bump size is varied such as bump protrusion, bump bridge, and bump discoloration. Experimental results exhibit that the proposed algorithm shows large improvement comparable to the other conventional boundary detection algorithms.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.663-670
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• 2019

The modified Canny edge detection algorithm that can detect the boundary between screen door and platform in the subway is proposed in this paper. Generally, in the subway, the boundary line between the platform and the screen door is darker than the surrounding area. Therefore, an edge image is using the modified bottom-hat transform by considering its characteristics. Double thresholded images with strong edge and weak edge through double thresholding are obtained. An algorithm that detects the boundary invasion between the platform and the screen door is proposed by calculating the length by applying the Hough transform to the double thresholded image and comparing the boundary line length between when there is an object such as a person and when there is no object. In this paper, the results of the proposed modified Canny edge detection algorithm using two different input images according to camera height position are shown by computer simulation.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.75-80
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• 2008

This paper proposes a method to detect scene change using global decision tree that extract boundary cut that have width of big change that happen by camera brake from difference value of frames. First, calculate frame difference value through regional X2-histogram and normalization, next, calculate distance between difference value using normalization. Shot boundary detection is performed by compare global threshold distance with distance value for two adjacent frames that calculating global threshold distance based on distance between calculated difference value. Global decision tree proposed this paper can detect easily sudden scene change such as motion from object or camera and flashlight.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.171-174
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• 2010

본 논문에서는 렌즈의 흠집을 추출할 수 있는 퍼지 기법을 이용한 렌즈 흠집 검출 방법을 제안한다. 제안된 방법은 렌즈 영상을 그레이 영상으로 변환한 후, 캐니 마스크를 이용하여 렌즈의 경계선을 추출한다. 추출된 렌즈의 경계선에 대해 평균 이진화와 모폴로지를 이용하여 렌즈 경계선을 보정한다. 렌즈 경계선이 보정된 영상에서 Seed Fill 알고리즘을 적용하여 렌즈의 내부 영역만을 추출한다. 추출된 렌즈의 내부 영역에 해당하는 원 영상에서 소벨 마스크를 적용하여 렌즈 내부 영역의 에지를 추출한다. 렌즈 내부 영역에서 추출된 에지 객체들의 정보를 이용하여 흠집과 비흠집을 분류하는 퍼지 기법을 적용하여 흠집 영역을 추출한다. 본 논문에서 제안된 렌즈의 흠집 검출 방법의 성능을 평가하기 위해 CHEMI, MID, HL, HM 시력 보정용 렌즈를 대상으로 실험한 결과, 제안된 방법이 흠집을 효과적으로 검출하는 것을 확인하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.12 no.4
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• pp.405-413
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• 1987

In this paper, we have discussed three-type median filters(SQUARE, CROSS, X-SHAPE) that preserving edge in an original image while reducing random noise was introduced for image enhancement and edge detection on radar image. Since radar image have a number of parts of curve, we compared results produced by edge detection operater proposed for improving the parts of curve with results of using the existing edge detection methods, such as Roberts, Sobel, Prewitt, Laplacian and Kirsch.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.6
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• pp.778-786
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• 2002

Scene boundary detection is important in the understanding of semantic structure from video data. However, it is more difficult than shot change detection because scene boundary detection needs to understand semantics in video data well. In this paper, we propose a new approach to scene segmentation using contextual information in video data. The contextual information is divided into two categories: local and global contextual information. The local contextual information refers to the foreground regions' information, background and shot activity. The global contextual information refers to the video shot's environment or its relationship with other video shots. Coherence, interaction and the tempo of video shots are computed as global contextual information. Using the proposed contextual information, we detect scene boundaries. Our proposed approach consists of three consecutive steps: linking, verification, and adjusting. We experimented the proposed approach using TV dramas and movies. The detection accuracy of correct scene boundaries is over than 80%.

• Progress in Medical Physics
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• v.7 no.2
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• pp.79-90
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• 1996

In this paper, we present an automatic threshold decision method to detect the contour of the a 2-D echocarodiogram by using the Bayes estimator for the boundary-like region. The boundary-like region is constructed from the conduction coefficient of the heat anisotro-pic diffusion method which enforces the blurred image during the preprocessing step. For the boundary-like region, we used the Bayes estimator to select an optimal threshold level. From this threshold value, the contour of the echocardigrams can be detected automatically Finally by overlapping the estimated contour to the original echocardiogram, we can obtain the contour enforced ultrasound echocardiogram.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.1041-1044
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• 2005

홍채인식 시스템에 있어서 동공 검출은 가장 먼저 이루어져아 할 전처리 과정이다. 현재 홍채인식 시스템에 있어서 사용되는 동공 검출은 영상의 모든 위치에서 원형돌출부(circular projection)를 구한 후, 경계선을 검출하여 원형의 경계 성분이 가장 강한 위치를 찾는 방법으로 연산량이 너무 많은 단점을 가지고 있다. 본 논문에서 제안하는 알고리즘은 같은 고주파성분에 해당 되더라도 경계선의Amplitude는 잡음의 경계선에 비해 그 값이 크다는 것을 이용하여, 경계선과 잡음을 구별할 수 있게 되고, 따라서 잡음 제거 성능을 기존의 방법에 비하여 상당히 향상시킨 웨이블렛 변환을 이용하여 동공의 특징을 추출할 수 있었다.

• Journal of Broadcast Engineering
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• v.15 no.4
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• pp.474-486
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• 2010

In this paper, we propose a new method for detection moving object contour using spatial and temporal edge. In general, contour pixels of the moving object are likely present around pixels with high gradient value along the time axis and the spatial axis. Therefore, we can detect the contour of the moving objects by finding pixels which have high gradient value in the time axis and spatial axis. In this paper, we introduce a new computation method, termed as temporal edge, to compute an gradient value along the time axis for any pixel on an image. The temporal edge can be computed using two input gray images at time t and t-2 using the Sobel operator. Temporal edge is utilized to detect a candidate region of the moving object contour and then the detected candidate region is used to extract spatial edge information. The final contour of the moving object is detected using the combination of these two edge information, which are temporal edge and spatial edge, and then the post processing such as a morphological operation and a background edge removing procedure are applied to remove noise regions. The complexity of the proposed method is very low because it dose not use any background scene and high complex operation, therefore it can be applied to real-time applications. Experimental results show that the proposed method outperforms the conventional contour extraction methods in term of processing effort and a ghost effect which is occurred in the case of entropy method.