• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.2
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• pp.1414-1419
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• 2015

A method for detecting a skin region on the image is generally used to detect the color information. However, If saturation lowered, skin detection is difficult because hue information of the pixels is lost. So in this paper, we propose a method of correcting color of lower saturation of skin region images by the lighting. Color correction process of this method is saturation image acquisition and low-saturation region classification, segmentation, and the saturation of the split in the low saturation region extraction and color values, the color correction sequence. This method extracts the low saturation regions in the image and extract the color and saturation in the region and the surrounding region to produce a color similar to the original color. Therefore, the method of extracting the low saturation region should be correctly preceding. Because more accurate segmentation in the process of obtaining a low saturation regions, we use a multi-threshold method proposed Otsu in Hue values of the HSV color space, and create a binary image. Our experimental results for 170 portrait images show a possibility that the proposed method could be used efficiently preprocessing of skin color detection method, because the detection result of proposed method is 5.8% higher than not used it.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1367-1383
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• 2007

A sensor network consists of a network of sensors that can perform computation and also communicate with each other through wireless communication. Some important characteristics of sensor networks are that the network should be self administered and the power efficiency should be greatly considered due to the fact that it uses battery power. In sensor networks, when large amounts of various stream data is produced and multiple queries need to be processed simultaneously, the power efficiency should be maximized. This work proposes a technique to create an index on multiple monitoring queries so that the multi-query processing performance could be increased and the memory and power could be efficiently used. The proposed SMILE tree modifies and combines the ideas of spatial indexing techniques such as k-d trees and R+-trees. The k-d tree can divide the dimensions at each level, while the R+-tree improves the R-tree by dividing the space into a hierarchical manner and reduces the overlapping areas. By applying the SMILE tree on multiple queries and using it on stream data in sensor networks, the response time for finding an indexed query takes in some cases 50% of the time taken for a linear search to find the query.

• Journal of the Korea Computer Graphics Society
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• v.2 no.1
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• pp.77-85
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• 1996

Using a series of medical tomograms, we can reconstruct internal organs or other objects of interest and generate 3-D images. It is generally accepted that the axial resolution determined by two sequential image slices is lower than the planar resolution in one image slices. Therefore, various methods of interpolation were developed for an accurate display of reconstructed images. In this paper, a new algorithm for 3-D reconstruction of the medical images such as MRI and X-ray CT is suggested. The algorithm is shape-based and utilizes parts of the gray-level information. We extend the conventional shape-based interpolation of the binary images to the gray-scale images using the shortest distance map. Using this new algorithm, We could reduce the execution time for interpolation while keeping similar high quality of the reconstructed images with reduced execution time and is applicable to the various medical tomograms.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.11
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• pp.1307-1314
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• 2015

This study proposed a more stable robust recognition algorithm which detects faces reliably even in cases where there are changes in lighting and angle of view, as well it satisfies efficiency in calculation and detection performance. The algorithm proposed detects the face area alone after normalization through pre-processing and obtains a feature vector using (PCA). Also, by applying the feature vector obtained for SVM, face areas can be tested. After the testing, the feature vector is applied to LDA and using Euclidean distance in the 2nd dimension, the final analysis and matching is performed. The algorithm proposed in this study could increase the stability and accuracy of recognition rates and as a large amount of calculation was not necessary due to the use of two dimensions, real-time recognition was possible.

• Journal of Korea Water Resources Association
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• v.41 no.12
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• pp.1231-1244
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• 2008

The objective of this study is to present a methodology for estimating runoff curve number(CN) using SWAT model which is capable of reflecting watershed heterogeneity such as climate condition, land use, soil type. The proposed CN estimation method is based on the asymptotic CN method and particularly, it uses surface flow data simulated by SWAT. This method has advantages to estimate spatial CN values according to subbasin division and to reflect watershed characteristics because the calibration process has been made by matching the measured and simulated streamflows. Furthermore, the method is not sensitive to rainfall-runoff data since CN estimation is on a daily basis. The SWAT based CN estimation method is applied to Chungju dam watershed. The regression equation of the estimated CN that exponentially decays with the increase of rainfall is presented.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.1
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• pp.45-52
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• 2015

The interoperability of multi-source data has become more important due to various digital maps, produced from public institutions and enterprises. In this study, the automatic matching algorithm of multi-source building data using hierarchical matching was proposed. At first, we divide digital maps into blocks and perform the primary geometric registration of buildings with the ICP algorithm. Then, corresponding building pairs were determined by evaluating the similarity of overlap area, and the matching threshold value of similarity was automatically derived by the Otsu binary thresholding. After the first matching, we extracted error matching candidates buildings which are similar with threshold value to conduct the secondary ICP matching and to make a matching decision using turning angle function analysis. For the evaluation, the proposed method was applied to representative public digital maps, road name address map and digital topographic map 2.0. As a result, the F measures of matching and non-matching buildings increased by 2% and 17%, respectively. Therefore, the proposed method is efficient for the matching of building polygons from multi-source digital maps.

• The KIPS Transactions:PartA
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• v.11A no.7 s.91
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• pp.555-562
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• 2004

Both global volume reduction and local shape changes of hippocampus within the brain indicate their abnormal neurological states. Hippocampal shape analysis consists of two main steps. First, construct a hippocampal shape representation model ; second, compute a shape similarity from this representation. This paper proposes a novel method for the analysis of hippocampal shape using integrated Octree-based representation, containing meshes, voxels, and skeletons. First of all, we create multi-level meshes by applying the Marching Cube algorithm to the hippocampal region segmented from MR images. This model is converted to intermediate binary voxel representation. And we extract the 3D skeleton from these voxels using the slice-based skeletonization method. Then, in order to acquire multiresolutional shape representation, we store hierarchically the meshes, voxels, skeletons comprised in nodes of the Octree, and we extract the sample meshes using the ray-tracing based mesh sampling technique. Finally, as a similarity measure between the shapes, we compute $L_2$ Norm and Hausdorff distance for each sam-pled mesh pair by shooting the rays fired from the extracted skeleton. As we use a mouse picking interface for analyzing a local shape inter-actively, we provide an interaction and multiresolution based analysis for the local shape changes. In this paper, our experiment shows that our approach is robust to the rotation and the scale, especially effective to discriminate the changes between local shapes of hippocampus and more-over to increase the speed of analysis without degrading accuracy by using a hierarchical level-of-detail approach.