• Journal of KIISE:Computer Systems and Theory
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• v.28 no.1_2
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• pp.20-32
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• 2001

각 장기는 고유한 명암값의 범위와 각 명암값에 대한 서로 다른 비율을 지니고 있으므로 제안된 연구에서는 이러한 명암값의 비율을 이용하여 장기의 영역과 노이즈를 구분할 수 있도록 하였다. 장기의 영역을 세 종류의 메쉬영상으로 표현하여 이들의 유니온 영상으로 장기의 전반적인 형태인 템플리트를 생성하였다. 템플리트 방식은 기존의 방식에서 명암값의 범위가 같은 노이즈의 제거가 어려운 단점을 해결하여 장기의 영역만을 분리할 수 있었다. 장기의 위치를 탐색하기 위한 위치탐색과정에서는 장기의 존재여부의 파악과 함께 분리된 장기까지 추적할 수 있도록 하였다. 외곽선 표현을 위해서는 템플리트로 이진영상에서 서브트랙션(subtraction)하는 방법을 사용하여 장기의 말단부위까지 세밀하게 표현하였다. 제안된 연구에서 사용된 오프닝과 클로징 방법으로 기존의 structuring element를 사용하는 방법에 비해 처리속도를 단축시킬 수 있었다. 추출된 장기의 면적을 토대로 체적계산을 시행하였고 동물실험을 통하여 임상 실험치를 제시하였다.

• Journal of Convergence for Information Technology
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• v.7 no.2
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• pp.77-82
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• 2017

In this paper, a new security algorithm to recognize the type of the vehicle with the vehicle image as a input image is suggested. The vehicle recognition security algorithm is composed of five core parts, such as the input image, background removal, edge areas extraction, pre-processing(binarization), and the vehicle recognition. Therefore, the final recognition rate of the security algorithm for vehicle type recognition can be affected by the function and efficiency of each step. After inputting image into a gray scale image and removing backgrounds, the binarization is performed by extracting only the edge region. After the pre-treatment process for making outlines clear, the type of vehicles is categorized into large vehicles, passenger cars and motorcycles through the ratio of height and width of the vehicle.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.4
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• pp.444-450
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• 1999

This paper deals with several methods: the clustering method that uses k-means algorithm to abstract the area of characters on the image document and the distance function that suits for the HIS coordinate system to cluster the image. For the prepossessing step to recognize this, or the method of characters segmentate, the algorithm to abstract a discrete character is also proposed, using the linking picture element. This algorithm provides the feature that separates any character such as the touching or overlapped character. The methods of projecting and tracking the edge have so far been used to segment them. However, with the new method proposed here, the picture element extracts a discrete character with only one-time projection after abstracting the character string. it is possible to pull out it. dividing the area into the character and the rest (non-character). This has great significance in terms of processing color documents, not the simple binary image, and already received verification that it is more advanced than the previous document processing system.

• Journal of the Korea Society of Computer and Information
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• v.20 no.5
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• pp.13-20
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• 2015

In this paper, we propose an algorithm that can recognize not only the number of stretched fingers but also determination of attached fingers for extracting features required for hand gesture recognition. The proposed algorithm detects the hand area in the input image by the skin color range filter based on a color model and labeling, and then recognizes various hand gestures by extracting the number of stretched fingers and determination of attached fingers using curvature information extracted from outlines and feature points. Experiment results show that the recognition rate and the frame rate are similar to those of the conventional algorithm, but the number of gesture cases that can be defined by the extracted characteristics is about four times higher than the conventional algorithm, so that the proposed algorithm can recognize more various gestures.

• Journal of Broadcast Engineering
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• v.2 no.2
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• pp.114-124
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• 1997

In object based coding, binary shape ccx:ling plays an important role by ccx:ling the outer shape of object. Here we propose a new shape ccx:ling tool, which enccx:les the outline of shape from a baseline. Different from 2-D (Vertex) shape ccx:ling algorithms. the proposed method encodeds the data that are extracted in a I-D fashion. The enccx:led data consist of the starting position, distance lists, and turning point lists. In the lossless ccx:ling mode, every contour pixel is input for ccx:ling, whereas variable sampling has been employed to enccx:le fewer contour pixels while preserving reasonable distortion. For interframe ccx:ling, a fast motion compensation was achieved by use of distance and turning point lists. Subjective viewing tests proved that the proposed method outperforms the current shape ccx:ling standard, CAE, in MPEG-4. In objective results for compression efficiency, the proposed method was significantly better in intraframe coding than CAE, whereas CAE was better in interframe ccx:ling.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.151-159
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• 2013

The building information should be up-to-date information and propagated rapidly for urban modeling, terrain analysis, life information, navigational system, and location-based services(LBS), hence the most recent and updated data of the building information have been required of researchers. This paper presents the developed system to extract the 3-dimension spatial information from aerial orthoimage and LiDAR data of HSI color model. In particular, this paper presents the image processing algorithm to extract the outline of specific buildings and generate the building polygon from the image using HIS color model, recursive backtracking algorithm and the search maze algorithm. Also, this paper shows the effectivity of the HIS color model in the image segmentation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.4
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• pp.335-341
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• 2006

This paper aims at developing an efficient method that extracts building using local spatial association of raw LiDAR data without setting up empirical variables such as a minimum building area, and applying the method to survey data to evaluate the efficiency of that. To do this, LISA(Local Indicatiors of Spatial Association) statistics are used which reflect local variations that can be appeared in the research area. It can be also a preprocess that detects spatial outliers through the significance test of LISA statistics and interpolate using kernel estimation. Boundaries of buildings as well as buildings can be extracted based on quadrant of Moran Scatterplot. Experimental results show that the proposed method is promising in extracting buildings from LiDAR data automatically.

• Journal of Broadcast Engineering
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• v.13 no.2
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• pp.236-244
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• 2008

We propose a new building detection and description algorithm for Lidar data and photogrammetric imagery using color segmentation, line segments matching, perceptual grouping. Our algorithm consists of two steps. In the first step, from the initial building regions extracted from Lidar data and the color segmentation results from the photogrammetric imagery, we extract coarse building boundaries based on the Lidar results with split and merge technique from aerial imagery. In the secondstep, we extract precise building boundaries based on coarse building boundaries and edges from aerial imagery using line segments matching and perceptual grouping. The contribution of this algorithm is that color information in photogrammetric imagery is used to complement collapsed building boundaries obtained by Lidar. Moreover, linearity of the edges and construction of closed roof form are used to reflect the characteristic of man-made object. Experimental results on multisensor data demonstrate that the proposed algorithm produces more accurate and reliable results than Lidar sensor.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.5
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• pp.411-419
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• 2013

Research on developing algorithms for building modeling such as extracting outlines of the buildings and segmenting patches of the roofs using aerial images or LiDAR data are active. However, utilizing information from the building model is not well implemented yet. This study aims to propose a scheme for search identical or similar shape of buildings by utilizing graph topology pattern matching under the assumptions: (1) Buildings were modeled beforehand using imagery or LiDAR data, or (2) 3D building data from digital maps are available. Side walls, segmented roofs and footprints were represented as nodes, and relationships among the nodes were defined using graph topology. Topology graph database was generated and pattern matching was performed with buildings of various shapes. The results show that efficiency of the proposed method in terms of reliability of matching and database structure. In addition, flexibility in the search was achieved by altering conditions for the pattern matching. Furthermore, topology graph representation could be used as scale and rotation invariant shape descriptor.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.2
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• pp.34-42
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• 1997

This paper deals with the recognition of closed planar shape using a three dimensional spectral feature vector which is derived from the FFT(Fast Fourier Transform) spectrum of contour sequence and fuzzy ARTMAP neural network classifier. Contour sequences obtained from 2-D planar images represent the Euclidean distance between the centroid and all boundary pixels of the shape, and are related to the overall shape of the images. The Fourier transform of contour sequence and spectrum analyzer are used as a means of feature selection and data reduction. The three dimensional spectral feature vectors are extracted by spectrum analyzer from the FFT spectrum. These spectral feature vectors are invariant to shape translation, rotation and scale transformation. The fuzzy ARTMAP neural network which is combined with two fuzzy ART modules is trained and tested with these feature vectors. The experiments including 4 aircrafts and 4 industrial parts recognition process are presented to illustrate the high performance of this proposed method in the recognition problems of noisy shapes.