• Journal of Digital Contents Society
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• v.17 no.5
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• pp.441-448
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• 2016

In this paper, we propose a method that segments the image, extracts its slope and compensate it in the image that text and background are mixed. The proposed method uses morphology based preprocessing and extracts the edges using canny operator. And after segmenting the image which the edges are extracted, it excludes the areas which the edges are included, only uses the area which the edges are included and creates the projection histograms according to their various direction slopes. Using them, it takes a slope having the greatest edge concentrativeness of each area and compensates the slope of the scene. On extracting the slope of the mixed scene of the text and background, the method can get better results as 0.7% than the existing methods as it excludes the useless areas that the edges do not exist.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.26-35
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• 2009

In this paper, we present morphology-based step region extraction and regularized iterative point-spread-function (PSF) estimation methods. The proposed PSF estimation method uses canny edge detector to extract the edge of the input image. We extract feasible vertical and horizontal edges using morphology analysis, such as the hit-or-miss transform. Given extracted edges we estimate the optimal step-response using flattening and normalization processes. The PSF is finally characterized by solving the equation which relates the optimal step response and the 2D isotropic PSF. We shows the restored image by the estimated PSF. The proposed algorithm can be applied a fully digital auto-focusing system without using mechanical focusing parts.

• Smart Media Journal
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• v.5 no.1
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• pp.38-43
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• 2016

As smart environment is spread out in our living environments, the needs of an approach related to Human Computer Interaction(HCI) is increases. One of them is head pose estimation. it related to gaze direction estimation, since head has a close relationship to eyes by the body structure. It's a key factor in identifying person's intention or the target of interest, hence it is an essential research in HCI. In this paper, we propose an approach for head pose estimation with pre-defined several directions by random forest classifier. We use canny edge detector to extract feature of the different facial image which is obtained between input image and averaged frontal facial image for extraction of rotation information of input image. From that, we obtain the binary edge image, and make two accumulated histograms which are obtained by counting the number of pixel which has non-zero value along each of the axes. This two accumulated histograms are used to feature of the facial image. We use CAS-PEAL-R1 Dataset for training and testing to random forest classifier, and obtained 80.6% accuracy.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.4
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• pp.333-337
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• 2002

A content-based image retrieval method using color, texture, and shape features is proposed in this paper. A region segmentation technique using PIM(Picture Information Measure) entropy is used for similarity indexing. For segmentation, a color image is first transformed to a gray image and it is divided into n$\times$n non-overlapping blocks. Entropy using PIM is obtained from each block. Adequate variance to perform good segmentation of images in the database is obtained heuristically. As variance increases up to some bound, objects within the image can be easily segmented from the background. Therefore, variance is a good indication for adequate image segmentation. For high variance image, the image is segmented into two regions-high and low entropy regions. In high entropy region, hue-saturation-intensity and canny edge histograms are used for image similarity calculation. For image having lower variance is well represented by global texture information. Experiments show that the proposed method displayed similar images at the average of 4th rank for top-10 retrieval case.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.22 no.12
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• pp.1084-1088
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• 2009

The measurement of dynamic stagger in electric railways is one of the key test parameters to increase speed and maintain safety in electric railways. This paper is introduces a non-contact optical-based measuring instrument of a catenary system in electric railways. The instrument is implemented by utilizing a CCD (Charge Coupled Device) camera installed on the roof of a vehicle for vision acquisition and image processing techniques including the Canny edge detector and the Hough transform to detect contact wires and calculate dynamic stagger. To check the validity of our approach for the intended application, we measured stagger of a overhead wire of a Korea Tilting Train (TTX). The non-contact optical-based measurement system proposed in this paper performs real-time stagger measurement of an activated high-voltage contact wire. By results of this paper, the instrument should be applied to assess performance and reliability of newly developed electric railway vehicles.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.1661-1664
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• 2005

본 논문에서는 computer-aided analysis 의 일환으로 X-ray 심혈관 조영도를 이용하여 관상동맥의 구조를 보여주는 방법에 대해 제시하고자 한다. 관상동맥 폐색증 환자들에게 시술되는 스텐트 삽입 시술이나 관상동맥 우회로 시술을 할 때에는 X-ray 의 조영 영상이 매우 중요한 시술의 기준이 되고 있으며, 조영 영상에서 혈관을 빠르고 정확하게 인식하는 것은 시술의 필수 조건이다. 이러한 시술중의 혈관구조 인식을 돕기 위하여 본 논문에서는 심혈관 조영 영상으로부터 관상동맥의 골격을 추출하기 위한 방법을 제안한다. 본 논문에서는 혈관 구조 추출을 위하여 3 단계 알고리즘을 제시한다. 첫번째 단계에서는 조영도에서 잡음을 제거하기 위하여 동질영역을 블러링할 수 있는 speckle reducing anisotropic diffusion 을 이용한 이미지 필터링을 수행한다. 이 필터링은 영상내 잡음을 제거하고 혈관의 경계선을 강화하여 정확한 영상인식을 가능하게 한다. 두번째 단계에서는 영상 내에서 보여지는 주요 혈관을 분할하는 것이다. 이 영상분할에는 canny edge detection 과 개선된 영역확장법(adaptive region growing)을 동시에 이용하는 복합적 분할기법이 수행된다. 세번째 단계에서는 형태학적 기법(Morphology)을 이용하여 분할결과의 부족한 부분을 보완하고 골격화를 수행하여 정확한 혈관 구조를 추출해낸다. 실험을 위해서는 정상인의 관상동맥 영상 뿐 아니라 혈관이 가늘어지는 폐색이 관찰되는 환자의 영상에 대해서도 실험하였다. 또한 논문에서 제시한 알고리즘에 대한 검증을 위하여 실험 결과들은 의료진의 감수를 거쳤다.

• Journal of the Korean Society of Combustion
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• v.20 no.1
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• pp.24-31
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• 2015

Flame structure, which contains a useful information for studying combustion instability of the flame, is often quantitatively visualized with PLIF (planar laser-induced fluorescence) and/or chemiluminescence images. The latter, a line-integral of a flame property, needs to be preprocessed before being inverted, mainly due to its inherent noise and the axisymmetry assumption of the inversion. A preprocessing scheme utilizing multi-division of ROI (region of interest) of the chemiluminescence image is proposed. Its feasibility has been tested with OH PLIF and $OH^*$ chemiluminescence images of SNG (synthetic natural gas) swirl-stabilized flames taken from a model gas turbine combustor. It turns out that the multi-division technique outperforms two conventional ones: those are, one without preprocessing and the other with uni-division preprocessing, reconstructing the SNG flame structure much better than its two counterparts, when compared with the corresponding OH PLIF images. It is also found that the Canny edge detection algorithm used for detecting edges in the multi-division method works better than the Sobel algorithm does.

• Textile Coloration and Finishing
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• v.20 no.1
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• pp.48-56
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• 2008

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 are one of the frequently occurring defects. Two algorithms used were compared according to both their processing time and detection rate. First algorithm (algorithm A) was based on morphological image processing such as dilation and opening for effective treatment of defective printing areas while second one (algorithm B) mainly employs well-defined edge detection technique based on canny detector and Zermike moment. It was concluded' that although both algorithms were quite successful, algorithm B showed relatively consistent performance than algorithm A in detecting complex patterns.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.449-450
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• 2007

오래 전 부터 영상처리와 컴퓨터 비전은 많은 분야에 응용되고 발전 되어 왔다. 그러한 기술 중에 최근 각광 받고 있는 그래프 짓(Graph cut) 알고리즘은 에너지함수를 최소화 하는 가장 강력한 최적화 기법중 하나이다. 그리고 일반적으로 Sobel, Prewitt, Roberts, Canny 에지(edge) 검출기 등은 영상처리에서 영상상의 에지를 검출하기 위해 이미 널리 사용되고 발전되어 온 기술이다. 물체에서의 윤곽만 검출하기 위해서는 우리가 원하지 않는 영상 위의 에지도 검출되기 때문에 예지 검출기만으로는 물체의 윤곽만을 검출하는 것은 불가능하다. 우리는 물체의 윤곽만 검출하기를 원하기 때문에 그래프 컷과 에지 검출기의 알고리즘을 결합하면 이러한 문제를 해결 할 수 있다는 것을 제안한다. 이 논문에서는 그래프 컷 알고리즘과 에지 검출기에 관해 간략하게 기술하고 그 결과를 보일 것이다.

• Journal of Korea Game Society
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• v.20 no.3
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• pp.45-54
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• 2020

An automated system using a embedded board is required to generate the notation input of the offline Go game. This paper integrates shape and color information of the objects on the Go game board for light-insensitive processing and reduces the computation step. This paper combined the detection of obstacles using connected components with the computation of canny edge detection and HSV-based detection. As a result, the processing time is reduced in the embedded environment so that reliable notation can be automatically stored even in real-time play environment.