• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.558-568
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• 2000

In the paper, we propose the automatic generation method of digital elevation map based on contour map. The proposed method classifies contour data and non-contour data by thinning and labelling process of the contour line and then connects smoothly broken contour line by Bezier curve. Finally, the digital devation map is generated by the interpolation using the height data of the contour line. The proposed method can reduce vest effort, time and expense which is spend to make digital elevation map.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.27-33
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• 2016

In this study we propose a method for 3D landform reconstruction and object modeling method by generating contour lines on the map using a depth sensor which abstracts characteristics of geological layers from the depth map. Unlike the common visual camera, the depth-sensor is not affected by the intensity of illumination, and therefore a more robust contour and object can be extracted. The algorithm suggested in this paper first abstracts the characteristics of each geological layer from the depth map image and rearranges it into the proper order, then creates contour lines using the Bezier curve. Using the created contour lines, 3D images are reconstructed through rendering by mapping RGB images of the visual camera. Experimental results show that the proposed method using depth sensor can reconstruct contour map and 3D modeling in real-time. The generation of the contours with depth data is more efficient and economical in terms of the quality and accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1169-1174
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• 1991

In conventional geographic mapping system, it is needed to input many already existing geographic map into computer system for secure and efficient maintence. Because of large map data, it is required to construct layers from map image for easy display, fast retreval and efficient storage. Thus this paper represents a method of the extracting features from contour map and constructing three layers. The layers are symbol, building, contour line. Experimental results are presented confirming the method's high extraction.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.153-163
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• 2004

This paper presents a video tracking method for a deformable moving object using an active contour model in the image sequences. It is quite important to decide the local convergence directions of the contour points for correctly extracting the boundary of the moving object with deformable shape. For this purpose, an energy function for the active contour model is newly proposed by adding a directional energy term using a frame difference map to tile Greedy algorithm. In addition, an updating rule of tile frame difference map is developed to encourage the stable convergence of the contour points. Experimental results on a set of synthetic and real image sequences showed that the proposed method can fully track the deformable object while extracting the boundary of the object elaborately in every frame.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.153-156
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• 2003

This paper proposes a video tracking method for a deformable moving object using an active contour model. In order to decide the convergent directions of the contour points automatically, a new energy function based on a frame difference map and an updating rules of the frame difference map are presented. Experimental results on a set of synthetic and real image sequences showed that the proposed method can fully track a speedy deformable object while extracting the boundary of the object exactly in every frame.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.234-237
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• 2009

CBL[1](Corner Block List)에 기반한 Non-Slicing 플로 플랜 알고리즘은 빈 공간이 없는 Non-Slicing 플로플랜만 나타낼 수 있다. 본 논문에서는 CBL 단점을 보완하고 실제 블록의 크기를 이용하여 최적의 위치에 블록을 배치 하기 위해 contour map을 이용할 것을 제시한다. 본 알고리즘은 배치시 면적을 최소화 하는 방법을 제시하므로 CBL의 단점을 해결하고 더불어 최적해를 찾기 위한 실행 시간을 단축 시키는 효과를 기대할 수 있다.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.4
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• pp.7-16
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• 2002

En this paper, we propose the algorithm that has analyzed the map Information automatically to extract the contour lines and numbers, symbols from the map image. After converting the input image to binary one, thinned image is obtained by thinning algorithm. The contour elements in the thinned image are classified and the classified elements are analyzed to automatically classify the numbers from symbols. Finally, the broken parts are restored by reconstruction algorithm. The performance of proposed algorithm is verified through the simulation. The proposed one has good performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5507-5528
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• 2016

In computer vision, salient object is important to extract the useful information of foreground. With active contour analysis acting as the core in this paper, we propose a bottom-up saliency detection algorithm combining with the Bayesian model and the global color distribution. Under the supports of active contour model, a more accurate foreground can be obtained as a foundation for the Bayesian model and the global color distribution. Furthermore, we establish a contour-based selection mechanism to optimize the global-color distribution, which is an effective revising approach for the Bayesian model as well. To obtain an excellent object contour, we firstly intensify the object region in the source gray-scale image by a seed-based method. The final saliency map can be detected after weighting the color distribution to the Bayesian saliency map, after both of the two components are available. The contribution of this paper is that, comparing the Harris-based convex hull algorithm, the active contour can extract a more accurate and non-convex foreground. Moreover, the global color distribution can solve the saliency-scattered drawback of Bayesian model, by the mutual complementation. According to the detected results, the final saliency maps generated with considering the global color distribution and active contour are much-improved.

• Journal of KIISE:Software and Applications
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• v.36 no.11
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• pp.901-911
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• 2009

In this paper, we propose a construction technique of two-level composite gradient map to automatically track a face with large movement in successive frames. Our method is composed of three main steps. First, the gradient maps with two-level resolution are generated for fast convergence of active contour. Second, to recognize the variations of face between successive frames and remove the neighbor background, weighted composite gradient map is generated by combining the composite gradient map and difference mask of previous and current frames. Third, to prevent active contour from converging local minima, the energy slope is generated by using closing operation. In addition, the fast closing operation is proposed to accelerate the processing time of closing operation. For performance evaluation, we compare our method with previous active contour model-based face tracking methods using a visual inspection, robustness test and processing time. Experimental results show that our method can effectively track the face with large movement and robustly converge to the optimal position even in frames with complicated background.

• Journal of Korea Multimedia Society
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• v.15 no.4
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• pp.492-500
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• 2012

In this paper, improved contour region coding method is proposed to accomplish better depth map coding performance. First of all, in order to use correlation between color video and depth map, a structure in SVC is applied to 3DVC. This can reduce bit-rate of the depth map while supporting the video to be transferred via various collection of network. As the depth map is mainly used to synthesize videos from different views, corrupted contour region can damage the overall quality of video. We hereby adapt a new differential quantization method when separating the contour region. The experimental results show that the proposed method can improve video quality by 0.06~0.5dB which translate the bit rate saving by 0.1~1.15%, when compared to the reference software.