• Journal of Korean Institute of Industrial Engineers
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• v.18 no.2
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• pp.11-22
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• 1992

Up to now, most researches on production automation have concentrated on local automation, e. g. CAD, CAM, robotics, etc. However, to achieve total automation it is required to link each local modules such as CAD, CAM into a unified and integrated system. One such missing link is between CAD and computer vision system. This thesis is an attempt to link the gap between CAD and computer vision system. In this paper, we propose algorithms that carry out edge detection, thinning and pruning from the image data of manufactured parts, which are obtained from video camera and then transmitted to computer. We also propose a feature extraction and surface determination algorithm which extract informations from the image data. The informations are compatible to IGES CAD data. In addition, we suggest a methodology to reduce search efforts for CAD data bases. The methodology is based on graph submatching algorithm in GEFG(Generalized Edge Face Graph) representation for each part.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.334-336
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• 2004

The postprocessing of fingerprint images is widely used in the elimination of the false minutiae caused by skeletonization. This paper presents the images were duplicated by The SOFM. And this Method showed that the good performance of eliminating false minutiae and fast processing.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.490-492
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• 2001

세선화 알고리즘은 문자 인식에서 인식율을 높이기 위한 전처리과정으로 대상물체에 대하여 1픽셀 두께가 될 때까지 적용시키는 알고리즘으로 그 중요성과 필요성으로 인하여 수많은 논문들이 발표되었다. 본 논문에서는 인터넷 정보검색을 목적으로 하는 회색조(Gray) 영상에 대한 이진화 및 세선화 알고리즘을 제안한다. 제안된 알고리즘은 해당 픽셀과 이웃 화소 간의 픽셀값 차이를 이용하여 일정값을 증감시키는 방법으로, 이미지의 중심으로 픽셀이 응집하게 하는 과정을 통해 이진화 및 세선화를 시켰으며, 병렬 구현이 용이하다. 제안된 알고리즘의 성능평가는 회색조 영상에 대해 기존 알고리즘들을 적용한 결과와 비교, 분석하여 소개하였다.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.411-420
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• 1999

In geology, lineament features have been used to identify geological events, and many of scientists have been developed the algorithm that can be applied with the computer to recognize the lineaments. We choose several edge detection filter, line detection filters and Hough transform to detect an edge, line, and to vectorize the extracted lineament features, respectively. firstly the edge detection filter using a first-order derivative is applied to the original image In this step, rough lineament image is created Secondly, line detection filter is used to refine the previous image for further processing, where the wrong detected lines are, to some extents, excluded by using the variance of the pixel values that is composed of each line Thirdly, the thinning process is carried out to control the thickness of the line. At last, we use the Hough transform to convert the raster image to the vector one. A Landsat image is selected to extract lineament features. The result shows the lineament well regardless of directions. However, the degree of extraction of linear feature depends on the values of parameters and patterns of filters, therefore the development of new filter and the reduction of the number of parameter are required for the further study.

• Journal of ILASS-Korea
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• v.6 no.1
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• pp.35-43
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• 2001

Previous studies on image processing techniques for panicle size measurement usually have focused on a single panicle or weakly overlapped particles. In the present work, the image processing algorithm for particle size measurement has been improved to process heavily-overlapped spherical-particle images. The algorithm consists of two steps; detection of boundaries which separate the images of the overlapped panicles from the background and the panicle identification process. For the first step, Sobel operator (using gray-level gradient) and the thinning process was adopted, and compared with the gray-level thresholding method that has been widely adopted. In the second, Hough transform was used. Hough transform is the detection algorithm of parametric curves such as straight lines or circles which can be described by several parameters. To reduce the measurement error, the process of finding the true center was added. The improved algorithm was tested by processing an image frame which contains heavily overlapped spherical panicles. The results showed that both the performances of detecting the overlapped images and separating the panicle from them were improved.

• Journal of Korea Multimedia Society
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• v.6 no.3
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• pp.419-428
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• 2003

Several methods have been studied to prune the parasitic branches that cause unfortunately from thinning a shape to get its skeleton. We found that the symmetric path finding method was most efficient because it followed the boundary pixels of the shape just once. In this paper, its extended method is proposed to apply to removing the noise branches that protrude out of the boundary of a segmented or extracted shape in a given image. The proposed method can remove a noise branch with one-pixel width and also remove the noise branch that includes a round shape called a noise blob. The method uses a 4-8-directional boundary-following technique to determine symmetric paths and finds noise branches with noise blobs by detecting quasi-symmetric paths. Its time complexity is a linear function of the number of boundary pixels. Interactively selectable parameters are used to define various types of noise branches flexibly, which are the branch - size parameter and the blob-size parameter. Experimental results for a practical shape and various artificial shapes showed that the proposed method was very useful for simplifying the shapes.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.2960-2970
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• 1997

In a variety of fields, recently, there is a growing interest in Geographic Information System which facilitates efficient storage and retrieval of geographic information. It is of extreme importance to make a good choice of efficient input method, because it takes the most of the lime and cost in constructing a GIS. Among several steps, thinning input image to produce skeleton of unit width is prerequisite to the automatic input or geographic maps. In this paper, we systematically evaluate the performance of representative thinning algorithms in geographic maps such as contour, cadastral, and water and sewer maps, and suggest appropriate algorithms for the maps, respectively. A thorough experiment indicates that Arcelli's method is best for contour maps, Holt's method for cadastral maps, and Chen's method for water and sewer maps.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.179-186
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• 1997

In this paper we suggest a development of surface defect inspection algorithms for cold mill strip. The defects which exist in a surface of cold mill strip have a scattering or singular distribution. This paper consists of preprocessing, feature extraction and defect classification. By preprocessing, the binarized defect image is achieved. In this procedure, Top-hit transform, adaptive thresholding, thinning and noise rejection are used. Especially, Top-hit transform using local min/max operation diminishes the effect of bad lighting. In feature extraction, geometric, moment and co-occurrence matrix features are calculated. For the defect classification, multilayer neural network is used. The proposed algorithm showed 15% error rate.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.3
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• pp.183-188
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• 2010

In this paper we propose a detection method of the medial axis of the continuous stripes on the LoG scale-space. Our method detects the medial axis of continuous stripes iteratively by varying the scale of LoG operator. Small-scale LoG operator detects two +/- pole pairs centered on the edge positions of stripe by the zero-crossing detection. The more increase the scale of LoG scale-space, the more close two poles to the medial axis of stripe. The medial axis of continuous stripe is the position where two poles is overlapped. The proposed method detected robustly the medial axis of continuous stripes stronger than the thinning methods used to binary image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.10 no.2
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• pp.69-75
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• 1985

The proposed seal identification procedure consists of the smoothing, rotation, thinning, and matching techniques. The seal images which are scanned by CCTV are thresholded into the binary prctures of $256{\times}256$ pixels through A/D converter and 6502 microcomputer. After the sample and target images are ratated into an identical orientation, a thinning process is used to extract the skeletons of the character strobes. The wighted map is constructed by distance weight from which the distance weighted correlation C is computed. The C is compared with the dicision constant C or C for the purpose of seal indentification. The identification rate is 95% and the total CPU time is less than 3 minutes for each identification in the experiment.