• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권12호
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• pp.5073-5086
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• 2015

The rock fracture detection by image analysis is significant for fracture measurement and assessment engineering. The paper proposes a novel image segmentation algorithm for the centerline tracing of a rock fracture based on Hessian Matrix at Multi-scales and Steger algorithm. A traditional fracture detection method, which does edge detection first, then makes image binarization, and finally performs noise removal and fracture gap linking, is difficult for images of rough rock surfaces. To overcome the problem, the new algorithm extracts the centerlines directly from a gray level image. It includes three steps: (1) Hessian Matrix and Frangi filter are adopted to enhance the curvilinear structures, then after image binarization, the spurious-fractures and noise are removed by synthesizing the area, circularity and rectangularity; (2) On the binary image, Steger algorithm is used to detect fracture centerline points, then the centerline points or segments are linked according to the gap distance and the angle differences; and (3) Based on the above centerline detection roughly, the centerline points are searched in the original image in a local window along the direction perpendicular to the normal of the centerline, then these points are linked. A number of rock fracture images have been tested, and the testing results show that compared to other traditional algorithms, the proposed algorithm can extract rock fracture centerlines accurately.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2373-2378
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• 2005

An emotion detection algorithm using frontal facial image is presented in this paper. The algorithm is composed of three main stages: image processing stage and facial feature extraction stage, and emotion detection stage. In image processing stage, the face region and facial component is extracted by using fuzzy color filter, virtual face model, and histogram analysis method. The features for emotion detection are extracted from facial component in facial feature extraction stage. In emotion detection stage, the fuzzy classifier is adopted to recognize emotion from extracted features. It is shown by experiment results that the proposed algorithm can detect emotion well.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.847-850
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• 2000

This paper proposes an image compressing and template matching algorithm for face image using GHA (Generalized Hebbian Algorithm). GHA is a part of PCA (Principal Component Analysis), that has single-layer perceptrons and operates and self-organizing performance. We used this algorithm for feature extraction of face shape, and our simulations verify the high performance for the proposed method. The shape for face in the fact that the eigenvector of face image can be efficiently represented as a coefficient that can be acquired by a set of basis is to compress data of image. From the simulation results, the mean PSNR performance is 24.08[dB] at 0.047bpp, and reconstruction experiment shows that good reconstruction capacity for an image that not joins at leaning.

• 한국정보통신학회논문지
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• 제17권8호
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• pp.1919-1925
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• 2013

본 논문은 스쿨존 영역의 교통 환경 분석을 위한 배경영상 추출 알고리즘을 제안하고 있다. 제안된 알고리즘은 교통 환경에서 수시로 발생되는 밝기 변화와 정지 객체에 의한 문제를 해결하고 있다. 전자를 위해 고속 Sigma-Delta 알고리즘을 이용해 배경영상을 현 프레임으로 고속 갱신하고, 후자를 위해 직전 프레임과 오랜 시간의 평균 배경영상을 이용해 동적 영역을 검출하여 정지 객체를 배경영상에서 배제한다. 실험 결과 제안된 알고리즘은 기존 알고리즘들과 비교하여 밝기 변화에 빠르게 잘 적응하고 있고, 배경영역의 SAD (Sum of Absolute Differences)를 약40~80% 정도를 줄여주고 있다.

• Journal of the Optical Society of Korea
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• 제18권5호
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• pp.523-530
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• 2014

Machine material and structural strain are critical factors for appraising mechanical properties and safety. Particularly in three and four-point bending tests, which appraise the deflection and flexural strain of an object due to external force, measurements are made by the crosshead movement or deflection meter of a universal testing machine. The Digital Image Correlation (DIC) method is one of the non-contact measurement methods. It uses the image analyzing method that compares the reference image with the deformed image for measuring the displacement and strain of the objects caused by external force. Accordingly, the advantage of this method is that the object's surface roughness, shape, and temperature have little influence. However, its disadvantage is that it requires extensive time to compare the reference image with the deformed image for measuring the displacement and strain. In this study, an algorithm is developed for DIC that can improve the speed of image analysis for measuring the deflection and strain of an object caused by a three-point bending load. To implement this algorithm for improving the speed of image analysis, LabVIEW 2010 was used. Furthermore, to evaluate the accuracy of the developed fast correlation algorithm, the deflection of an aluminum specimen under a three-point bending load was measured by using the universal test machine and DIC measurement system.

• 한국멀티미디어학회논문지
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• 제23권6호
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• pp.756-764
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• 2020

A typical algorithm used for image analysis is the Convolutional Neural Network(CNN). R-CNN, Fast R-CNN, Faster R-CNN, etc. have been studied to improve the performance of the CNN, but they essentially require large amounts of data and high algorithmic complexity., making them inappropriate for small and medium-sized services. Therefore, in this paper, the image label prediction algorithm based on CNN with collaborative layer with low complexity, high accuracy, and small amount of data was proposed. The proposed algorithm was designed to replace the part of the neural network that is performed to predict the final label in the existing deep learning algorithm by implementing collaborative filtering as a layer. It is expected that the proposed algorithm can contribute greatly to small and medium-sized content services that is unsuitable to apply the existing deep learning algorithm with high complexity and high server cost.

• 한국염색가공학회지
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• 제21권1호
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• pp.53-58
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• 2009

A real-time inspection system has been developed by combining CCD based image processing algorithm and a standard lighting equipment. The system was tested for defective fabrics showing nozzle contact scratch marks, which were one of the frequently occurring defects. Multi-resolution analysis(MRA) algorithm were used and evaluated according to both their processing time and detection rate. Standard value for defective inspection was the mean of the non-defect image feature. Similarity was decided via comparing standard value with sample image feature value. Totally, we achieved defective inspection accuracy above 95%.

• 한국지능시스템학회논문지
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• 제14권7호
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• pp.801-806
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• 2004

감성 인식 기술은 사회의 여러 분야에서 요구되고 있는 필요한 기술이지만, 인식 과정의 어려움으로 인해 풀리지 않는 문제로 낡아있다. 특히 얼굴 영상을 이용한 감정 인식 기술에서 얼굴 영상을 분석하는 기술 개발이 필요하다. 하지만 얼굴분석을 어려움으로 인해 많은 연구가 진행 중이다. 된 논문에서는 감정 인식을 위한 얼굴 영상 분석 알고리즘을 제안한다. 제안된 얼굴 영상 분석 알고리즘은 얼굴 영역 추출 알고리즘과 얼굴 구성 요소 추출 알고리즘으로 구성된다. 얼굴 영역 추출 알고리즘은 다양한 조명 조건에서도 강인하게 얼굴 영역을 추출할 수 있는 퍼지 색상 필터를 사용한 방법을 제안하였다. 또한 얼굴 구성 요소 추출 알고리즘에서는 가상 얼굴 모형을 이용함으로써 보다 정확하고 빠른 얼굴 구성 요소 추출이 가능하게 하였다. 최종적으로 모의실험을 통해 각 알고리즘들의 수행 과정을 살펴보았으며 그 성능을 평가하였다.

• Journal of Advanced Marine Engineering and Technology
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• 제23권2호
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• pp.259-269
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• 1999

A new algorithm for measuring 3-D velocity components of high speed flows were developed using a digital image processing technique. The measuring system consists of three CCD cameras an optical instrument called AOM a digital image grabber and a host computer. The images of mov-ing particles arranged spatially on a rotation plate are taken by two or three CCD cameras and are recorderd onto the image grabber or a video tape recoder. The three-dimensionl velocity com-ponents of the particles are automatically obtained by the developed algorithm In order to verify the validity of this technique three-dimensional velocity data sets obtained from a computer simu-lation of a backward facing step flow were used as test data for the algorithm. an uncertainty analysis associated with the present algorithm is systematically evaluated, The present technique is proved to be used as a tookl for the measurement of unsteady three-dimensional fluid flows.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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• pp.453-456
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• 2003

Compared with other features of the image, color features are less sensitive to noise and background complication. Besides, this adding to object segmentation has more accuracy of image retrieval. This paper presents object segmentation and HAQ(Histogram Analysis and Quantization) algorithm approach to extract features(the object information and the characteristic colors) of an image. The empirical results shows that this method presents exactly spatial and color information of an image as image retrieval's feature.