• Journal of the Korea Computer Graphics Society
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• v.8 no.2
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• pp.15-22
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• 2002

Image segmentation methods partition an image into meaningful regions. For image composition and analysis, it is desirable for the partitioned regions to represent meaningful objects in terms of human perception and manipulation. Despite the recent progress in image understanding, however, most of the segmentation methods mainly employ low-level image features and it is still highly challenging to automatically segment an image based on high-level meaning suitable for human interpretation. The concept of HCI (Human Computer Interaction) can be applied to operator-assisted image segmentation in a manner that a human operator provides guidance to automatic image processing by interactively supplying critical information about object boundaries. Intelligent Scissors and Snakes have demonstrated the effectiveness of human-assisted segmentation [2] [1]. This paper presents a method for interactive image segmentation for more efficient and effective detection and tracking of object boundaries. The presented method is partly based on the concept of Intelligent Scissors, but employs the well-established Canny edge detector for stable edge detection. It also uses "sewing method" for including weak edges in object boundaries, and 5-direction search to promote more efficient and stable linking of neighboring edges than the previous methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.2
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• pp.149-156
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• 2008

In this paper, we propose a method aiming at updating the building information of the digital maps using single high resolution satellite image and digital map. Firstly we produced a digital orthoimage through the automatic co-registration of QuickBird image and 1:1,000 digital map. Secondly we extracted building height information through the template matching of digital map's building vector data and the image's edges obtained by Canny operator. Finally we refined the shape of some buildings by using the result from template matching as the seed polygon of the greedy snake algorithm. In order to evaluate the proposed method's effectiveness, we estimated accuracy of the extracted building information using LiDAR DSM and 1:1,000 digital map. The evaluation results showed the proposed method has a good potential for extraction and revision of building information.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.1
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• pp.1-8
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• 2003

Various methods have been studying to maintain and apply the multimedia inform abruptly increasing over all social fields, in recent years. For retrieval of still images, we is implemented content-based image retrieval system in this paper that make possible to retrieve similar objects from image database after segmenting query object from background if user request query. Query image is processed median filtering to remove noise first and then object edge is detected it by canny edge detection. And query object is segmented from background by using convex hull. Similarity value can be obtained by means of histogram intersection with database image after securing color histogram from segmented image. Also segmented image is processed gray convert and wavelet transform to extract spacial gray distribution and texture feature. After that, Similarity value can be obtained by means of banded autocorrelogram and energy. Final similar image can be retrieved by adding upper similarity values that it make possible to not only robust in background but also better correct object retrieval by using object segmentation method.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.1
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• pp.1-11
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• 2018

Mapping accurate spatial information is important for constructing three-dimensional (3D) spatial models and managing artificial facilities, and, especially, mapping road centerlines is necessary for constructing accurate road maps. This research developed a semi-automatic methodology for mapping road centerlines using the MMS(Mobile Mapping System) LiDAR(Light Detection And Ranging) point cloud as follows. First, the intensity image was generated from the given MMS LiDAR data through the interpolation method. Next, the line segments were extracted from the intensity image through the edge detection technique. Finally, the road centerline segments were manually selected among the extracted line segments. The statistical results showed that the generated road centerlines had 0.065 m overall accuracy but had some errors in the areas near road signs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.83-86
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• 2013

In this paper, by using the Morphing, if the size of the eyes of both sides are not the same, we propose a method to correct the size of eyes area. First, by using the Haar-like feature from a input image that is input, to detect the shape of the eyes and face. After inverting the left and right eye region of one of the shape of the eyes detected sets the correspondence between the second with a line to control the shape of the eyes detected using eyes that is detected with canny edge, in the previous step. To the Warping to match the correspondence was then set in the previous step, an area of each eye. Then, I merge the image which merged in the eye area is detected from the original image. As a result, a system result of the experiment in the test image and face image seen from the front, the proposed, prove to be more efficient than a method of keying the size of the eye only.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.3 no.2 s.5
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• pp.19-28
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• 2004

This paper shows how to compensate the skew from the traffic sign included in the natural image and extract the text. The research deals with the Process related to the array image. Ail the process comprises four steps. In the first fart we Perform the preprocessing and Canny edge extraction for the edge in the natural image. In the second pan we perform preprocessing and postprocessing for Hough Transform in order to extract the skewed angle. In the third part we remove the noise images and the complex lines, and then extract the candidate region using the features of the text. In the last part after performing the local binarization in the extracted candidate region, we demonstrate the text extraction by using the differences of the features which appeared between the tett and the non-text in order to select the unnecessary non-text. After carrying out an experiment with the natural image of 100 Pieces that includes the traffic sign. The research indicates a 82.54 percent extraction of the text and a 79.69 percent accuracy of the extraction, and this improved more accurate text extraction in comparison with the existing works such as the method using RLS(Run Length Smoothing) or Fourier Transform. Also this research shows a 94.5 percent extraction in respect of the extraction on the skewed angle. That improved a 26 percent, compared with the way used only Hough Transform. The research is applied to giving the information of the location regarding the walking aid system for the blind or the operation of a driverless vehicle

• Journal of KIISE:Databases
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• v.36 no.4
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• pp.263-279
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• 2009

Shape features in a content-based image retrieval (CBIR) system are divided into two classes: contour-based and region-based. Contour-based shape features are simple but they are not as efficient as region-based shape features. Most systems using the region-based shape feature have to extract the region firs t. The prior works on region-based systems still have shortcomings. They are complex to implement, particularly with respect to region extraction, and do not sufficiently use the spatial relationship between regions in the distance model In this paper, a region extraction method that is the combination of an edge-based method and a region growing method is proposed to accurately extract regions inside an object. Edges inside an object are accurately detected based on the Canny edge detector and the Hough transform. And the modified Integrated Region Matching (IRM) scheme which includes the adjacency relationship of regions is also proposed. It is used to compute the distance between images for the similarity search using shape features. The experimental results show the effectiveness of our region extraction method as well as the modified IRM. In comparison with other works, it is shown that the new region extraction method outperforms others.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.497-503
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• 2005

본 논문에서는 퍼지 RBF 네트워크를 이용한 운송 컨테이너 식별자 인식 시스템을 제안한다. 일반적으로 운송 컨테이너의 식별자들은 크기나 위치가 정형화되어 있지 않고 외부 잡음으로 인하여 식별자의 형태가 변형될 수 있기 때문에 일정한 규칙으로 찾기는 힘들다. 본 논문에서는 이러한 특성을 고려하여 컨테이너 영상에 대해 Canny 마스크를 이용하여 에지를 검출하고, 검출된 에지 정보에서 영상획득 시 외부 광원에 의해 수직으로 길게 발생하는 잡음들을 퍼지 추론 방법을 적용하여 제거한 후에 수직 블록과 수평 블록을 검출하여 컨테이너의 식별자 영역을 추출하고 이진화한다. 이진화된 식별자 영역에 대해 검정색의 빈도수를 이용하여 흰바탕과 민바탕을 구분하고 4방향 윤광선 추적 알고리즘을 적용하여 개별 식별자를 추출한다. 개별 식별자 인식을 위해 퍼지 C-Means 알고리즘을 이용한 퍼지 RBF 네트워크를 제안하여 개별 식별자에 적용한다. 제안된 퍼지 RBF 네트워크는 퍼지 C-Means 알고리즘을 중간층으로 적용하고 중간층과 출력층 간의 학습에는 일반화된 델타 학습 방법과Delta-bar-Delta 알고리즘을 적용하여 학습 성능을 개선한다. 실제 컨테이너 영상을 대상으로 실험한 결과, 기존의 식별자 추출 방법보다 제안된 식별자 추출방법이 개선되었다. 그리고 기존의 ART2 기반 RBF 네트워크보다 제안된 퍼지 RBF 네트워크가 컨테이너 식별자의 학습 및 인식에 있어서 우수함을 확인하였다.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.3
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• pp.366-370
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• 2010

This paper presents an automatic Oriental ink-rendering technique that recreates the artistic style of Oriental paintings from a single image. In Oriental paintings are characterized by strokes with various thickness and disordered dispersion. In this study, a stroke drawing method was developed based on the canny edge detector and radial curvature that are suitable for lines with varied thickness even along a single stroke. A dispersion-shading method was likewise developed by applying a set of iterated dual-filtering, and intensity exaggeration methods. The dispersion-shading method is designed to increase the local shade details, to decrease the global shade. Unlike the existing watercolor-rendering and abstraction system the proposed dispersion-shading method achieves disordered shade details rather than simplification.

• Proceedings of the Korean Society of Computer Information Conference
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• 2009.01a
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• pp.173-176
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• 2009

본 논문에서는 피부색 정보와 눈, 입의 위치를 찾아 실시간으로 얼굴을 인식하는 랩을 제안한다. 먼저 노이즈를 제거하여 얼굴 후보 영역을 지정한다. 지정된 얼굴 후보 영역에서 눈과 입을 찾고, 찾은 눈과 입 사이의 영역에서 에지를 탐색하여 코의 존재 유무를 검증하고 이를 바탕으로 얼굴인지 판단하는 절차를 따른다. 제안한 기법은 피부색 검출을 위해 YCbCr 을 이용하여 피부 영역을 찾고 지정한 피부 영역에서 노이즈를 제거한 후, Eye Map의 EyeMapC 연산을 통해 눈을 Lip Map을 통해 입을 찾는다. 찾아낸 눈과 입의 사이의 영역에서 Canny Edge 연산을 수행하여 코의 존재 유무를 판단하여 최종적인 얼굴 영역을 판별하는 방법을 제안한다.