• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.1887-1890
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• 2003

This paper presents a three-dimensional (3D) head pose estimation algorithm using the stereo image. Given a pair of stereo image, we automatically extract several important facial feature points using the disparity map, the gabor filter and the canny edge detector. To detect the facial feature region , we propose a region dividing method using the disparity map. On the indoor head & shoulder stereo image, a face region has a larger disparity than a background. So we separate a face region from a background by a divergence of disparity. To estimate 3D head pose, we propose a 2D-3D Error Compensated-SVD (EC-SVD) algorithm. We estimate the 3D coordinates of the facial features using the correspondence of a stereo image. We can estimate the head pose of an input image using Error Compensated-SVD (EC-SVD) method. Experimental results show that the proposed method is capable of estimating pose accurately.

• 로봇학회논문지
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• 제8권2호
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• pp.82-91
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• 2013

This paper proposes a building recognition algorithm using watershed image segmentation algorithm and integrated region matching (IRM). To recognize a building, a preprocessing algorithm which is using Gaussian filter to remove noise and using canny edge extraction algorithm to extract edges is applied to input building image. First, images are segmented by watershed algorithm. Next, a region adjacency graph (RAG) based on the information of segmented regions is created. And then similar and small regions are merged. Second, a color distribution feature of each region is extracted. Finally, similar building images are obtained and ranked. The building recognition algorithm was evaluated by experiment. It is verified that the result from the proposed method is superior to color histogram matching based results.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2014년도 추계학술대회
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• pp.130-133
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• 2014

본 논문은 Laplacian of Gaussians (LoG)에 캐니 에지 검출 기법을 접목한 새로운 색상 보간 알고리듬을 제안한다. 캐니 에지 검출 기법은 영상 스무딩, 기울기 크기와 각도 계산, 세션화, 이중 문턱치 처리 과정으로 이루어진다. 이때 앞의 두 과정을 LoG를 이용하여 처리함으로써 기존의 캐니 애지 검출법보다 정확한 방향 정보를 얻을 수 있다. 실험결과를 통해 기존의 색상 보간 알고리듬에 비해 Peak Signal to Noise Ratio (CPSNR)이 상승함을 확인하였으며, 에지 영역 주변에서 발생하였던 무지개 에러가 현저히 감소하였음을 확인할 수 있었다.

• Journal of Astronomy and Space Sciences
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• 제33권4호
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• pp.313-318
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• 2016

Communication, Ocean And Meteorological Satellite (COMS) Meteorological Imager (MI) images are processed for radiometric and geometric correction from raw image data. When intermediate image data are matched and compared with reference landmark images in the geometrical correction process, various techniques for edge detection can be applied. It is essential to have a precise and correct edged image in this process, since its matching with the reference is directly related to the accuracy of the ground station output images. An edge detection method based on neural networks is applied for the ground processing of MI images for obtaining sharp edges in the correct positions. The simulation results are analyzed and characterized by comparing them with the results of conventional methods, such as Sobel and Canny filters.

• 전기학회논문지
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• 제67권12호
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• pp.1678-1684
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• 2018

Dental caries is one of the most popular oral disease. The aim of automatic dental cavity detection system is helping dentist to make accurate diagnosis. It is very important to separate cavity from the teeth in the detection system. In this paper, We compared two active contour algorithms, Snake and DRLSE(Distance Regularized Level Set Evolution). To improve performance, image is selected ROI(region of interest), then applied bilateral filter, Canny edge. In order to evaluate the algorithms, we applied to 7 tooth phantoms from incisor to molar. Each teeth contains two cavities of different shape. As a result, Snake is faster than DRLSE, but Snake has limitation to compute topology of objects. DRLSE is slower but those of performance is better.

• Computers and Concrete
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• 제10권2호
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• pp.135-147
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• 2012

At mesoscale, concrete is considered as a three-phase composite material consisting of the aggregate particles, the cement matrix and the interfacial transition zone (ITZ). The reconstruction of the internal structures for concrete composites requires the identification of the boundary of the aggregate particles and the cement matrix using digital imaging technology followed by post-processing through MATLAB. A parameter study covers the subsection transformation, median filter, and open and close operation of the digital image sample to obtain the optimal parameter for performing the image processing technology. The subsection transformation is performed using a grey histogram of the digital image samples with a threshold value of [120, 210] followed by median filtering with a $16{\times}16$ square module based on the dimensions of the aggregate particles and their internal impurity. We then select a "disk" tectonic structure with a specific radius, which performs open and close operations on the images. The edges of the aggregate particles (similar to the original digital images) are obtained using the canny edge detection method. The finite element model at mesoscale can be established using the proposed image processing technology. The location of the crack determined through the numerical method is identical to the experimental result, and the load-displacement curve determined through the numerical method is in close agreement with the experimental results. Comparisons of the numerical and experimental results show that the proposed image processing technology is highly effective in reconstructing the internal structures of concrete composites.

• 응용통계연구
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• 제32권5호
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• pp.721-740
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• 2019

영상처리 분야에서 중요한 분야인 잡음 제거는 통계적인 접근이 필요하지만 잡음에 대한 특정한 분포를 가정하기 어려우며 지역적 특징을 반영하는 공간 필터는 소표본에 해당하므로 모수적인 방법으로 접근할 수 없다. 1차 영상 미분과 2차 영상 미분은 영상에 포함된 잡음 수준에 따라 확연한 차이를 보이며 캐니 에지 검출기를 사용하면 보다 명확히 알 수 있다. 잡음 수준을 통계적으로 확인하고자 Fligner-Killeen 검정을 진행하고 붓스트랩 방법을 사용하였으며 추정된 잡음의 수준을 베타분포의 누적분포함수를 이용하여 0과 1사이의 값을 갖도록 하였다. 본 연구에서는 영상에 포함된 잡음 수준을 고려하는 잡음 제거 알고리즘을 제시하고자 한다.