• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.1
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• pp.39-45
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• 2022

In this paper, we propose methods to improve image-based auto-focus that can compensate for drawbacks of traditional auto-focus control. When adjusting the focus, there is a problem that the focus window cannot be set to the same position if the camera's LOS is not directed at the same location and flow or shake. To address this issue, we applied image tracking techniques to improve optimal focus localization accuracy. And also, although the same focus value should be calculated at the same focus step, but different values can be calculated by camera's fine shaking or image disturbance due to atmospheric scattering. To tackle this problem a SAFS (Stable Adjacency Frame Selection) has been proposed. As a result of this study, our proposed methodology shows more accurate than traditional methods in terms of finding best focus position.

• Journal of Korea Entertainment Industry Association
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• v.5 no.1
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• pp.127-133
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• 2011

Characters in natural image are an important information with various context. Previous work of character region detection algorithms is not detect of character region in case of image complexity and the surrounding lighting, similar background to character, so this paper propose an method of character region detection in natural image using edge and connected component by morphological reconstructions. Firstly, we detect edge using Canny-edge detector and connected component with local min/max value by morphological reconstructed-operation in gray-scale image, and labeling each of detected connected component elements. lastly, detected candidate of text regions was merged for generation for one candidate text region, Final text region detected by checking the similarity and adjacency of neighbor of text candidate individual character. As the results of experiments, proposed algorithm improved the correctness of character regions detection using edge and connected components.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.1
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• pp.111-121
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• 2006

Recently, many studies have been performed to apply airborne LIDAR data to extracting urban models. In order to model efficiently the man-made objects which are the main components of these urban models, it is important to extract automatically planar patches from the set of the measured three-dimensional points. Although some research has been carried out for their automatic extraction, no method published yet is sufficiently satisfied in terms of the accuracy and completeness of the segmentation results and their computational efficiency. This study thus aimed to developing an efficient approach to automatic segmentation of planar patches from the three-dimensional points acquired by an airborne LIDAR system. The proposed method consists of establishing adjacency between three-dimensional points, grouping small number of points into seed patches, and growing the seed patches into surface patches. The core features of this method are to improve the segmentation results by employing the variable threshold value repeatedly updated through a statistical analysis during the patch growing process, and to achieve high computational efficiency using priority heaps and sequential least squares adjustment. The proposed method was applied to real LIDAR data to evaluate the performance. Using the proposed method, LIDAR data composed of huge number of three dimensional points can be converted into a set of surface patches which are more explicit and robust descriptions. This intermediate converting process can be effectively used to solve object recognition problems such as building extraction.

• Journal of Environmental Science International
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• v.20 no.5
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• pp.565-574
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• 2011

This study analyzed the concentration of the heavy metals(Cd, Hg, iAs) of urine(n=576) from May, 2007 to Oct 2007. The subject was residents in G, Y, H industrial area, Jeollanam-do, in which exposure due to the adjacency of the industrial complex. As to the heavy metal concentration in the urine of the residents in the whole exposed region and the comparing region, the content of cadmium, mercury, and inorganic arsenic in the exposed region group were 1.23, 1.85, and 8.80 ${\mu}g$/g_ct respectively, and those of the comparing region group were 1.87, 2.00, and 8.93 ${\mu}g$/g_ct respectively, which indicates that the concentration of the comparing group was higher than that of the exposed group. The heavy metal concentration for each age group increased in proportion to age except those under 10 for some substances(p<0.01). As to geometric mean concentration cadmium and inorganic arsenic in urine according to the smoking history of the subject, the concentration of the smoking group and the non-smoking group were 1.65 ${\mu}g$/g_ct and 9.13 ${\mu}g$/g_ct respectively, while those of the non-smoking group were 1.47 ${\mu}g$/g_ct and 8.91 ${\mu}g$/g_ct respectively, which indicates that the former is higher than the latter. As to the inorganic arsenic concentration in urine according to the food preference, in order of vegetable, fish, and meat showed high concentration (p<0.01). To clarify the factors affecting the heavy metal concentration in urine among the subjects, the multiple regression analysis was conducted. As a result, it turned out that as to cadmium content in urine, gender, age, drinking, and smoking have influence on the subjects, with explanatory adequacy of 37.5 %.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.1003-1017
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• 2017

Multispectral image data of high spatial resolution is required to obtain correct information on the ground surface. The multispectral image data has lower resolution compared to panchromatic data. PAN-sharpening fusion technique produces the multispectral data with higher resolution of panchromatic image. Recently the object-based approach is more applied to the high spatial resolution data than the conventional pixel-based one. For the object-based image analysis, it is necessary to perform image segmentation that produces the objects of pixel group. Image segmentation can be effectively achieved by the process merging step-by-step two neighboring regions in RAG (Regional Adjacency Graph). In the satellite remote sensing, the operational environment of the satellite sensor causes image degradation during the image acquisition. This degradation increases variation of pixel values in same area, and results in deteriorating the accuracy of image segmentation. An iterative approach that reduces the difference of pixel values in two neighboring pixels of same area is employed to alleviate variation of pixel values in same area. The size of segmented regions is associated with the quality of image segmentation and is decided by a stopping rue in the merging process. In this study, the image restoration and segmentation was quantitatively evaluated using simulation data and was also applied to the three PAN-sharpened multispectral images of high resolution: Dubaisat-2 data of 1m panchromatic resolution from LA, USA and KOMPSAT3 data of 0.7m panchromatic resolution from Daejeon and Chungcheongnam-do in the Korean peninsula. The experimental results imply that the proposed method can improve analytical accuracy in the application of remote sensing high resolution PAN-sharpened multispectral imagery.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.668-676
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• 2016

This study reviewed the planning characteristics of contemporary Japanese middle school architecture on which related studies are insufficient, aiming to obtain new ideas for planning Korean middle school facilities. Fourteen case schools built after 1990s were selected and analyzed. They were divided into learning-living space and other major spaces. The planning characteristics of the case schools are summarized as follows 1) The case schools were classified into two categories, departmentalized classroom type (D type) and usual with variation type (UV type) by school system. These categories can also be the classification standard for basic architectural characteristics in learning and living space of case schools. 2) D type case schools have departmentalized classrooms, home base, media space and teacher's space for learning-living space. D type case schools are divided into 'attached-to-classroom type' and 'separate type' depending on the adjacency of the home base and departmentalized classroom. 3) UV type case schools have multipurpose space around the classroom for learning-living space and can be divided into two types, i.e., 'directly adjacent' and 'separate', depending on the connectivity to classroom of multipurpose room. 4) Specialized classrooms are designed to have the openness to the public and the own characteristics of school subjects strengthened and show the spatial differentiation with connected ancillary spaces. 5) Libraries are designed as complex zones grouped with computer labs, audio visual rooms and multipurpose halls not as a single room and as open plan not with a closed wall. 6) The gymnasium is the basic sports facility with a martial arts room and outdoor pool, which are for after-school activities as well as physical education class. 7) The terrace, balcony and outdoor stairs are frequently used architectural vocabularies as diverse outdoor spaces with a variety of functions.

• Korean Journal of Remote Sensing
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• v.29 no.2
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• pp.209-218
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• 2013

The Sonoran Desert, which is located in North America, has been frequently used for vicarious calibration of many optical sensors in satellites. Although the desert area has good conditions for vicarious calibration (e.g. high reflectance, little vegetation, large area, low precipitation), its adjacency to the sea and large variability in atmospheric water vapor are the disadvantages for vicarious calibration. For vicarious calibration using top-of-atmospheric (TOA) reflectance, the atmospheric variability brings about degraded precision in vicarious calibration results. In this paper, the location with the smallest radiometric variability in TOA reflectance is sought by using 12-year Landsat 5 data, and corrected the TOA reflectance for bidirectional reflectance distribution function (BRDF) which is another major source of variability in TOA reflectance. Experiments show that the mid-western part of the Sonoran Desert has the smallest variability collectively for visible and near-infrared bands, and the variability from the sunarget-sensor geometry can be reduced by the BRDF correction for the visible bands, but not sufficiently for the infrared bands.

• 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.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.93-98
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• 2013

Multi-temporal high resolution satellite images are essential data for efficient city analysis and monitoring. Yet even when acquired from the same location, identical sensors as well as different sensors, these multi-temporal images have a geometric inconsistency. Matching points between images, therefore, must be extracted to match the images. With images of an urban area, however, it is difficult to extract matching points accurately because buildings, trees, bridges, and other artificial objects cause shadows over a wide area, which have different intensities and directions in multi-temporal images. In this study, we analyze a shadow effect on image matching of high resolution satellite images in urban area using Scale-Invariant Feature Transform(SIFT), the representative matching points extraction method, and automatic shadow extraction method. The shadow segments are extracted using spatial and spectral attributes derived from the image segmentation. Also, we consider information of shadow adjacency with the building edge buffer. SIFT matching points extracted from shadow segments are eliminated from matching point pairs and then image matching is performed. Finally, we evaluate the quality of matching points and image matching results, visually and quantitatively, for the analysis of shadow effect on image matching of high resolution satellite image.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.1-11
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• 2006

Many research demonstrations and commercial applications have been tried to develop face detection and recognition systems. Human face detection plays an important role in applications such as access control and video surveillance, human computer interface, identity authentication, etc. There are some special problems such as a face connected with background, faces connected via the skin color, and a face divided into several small parts after skin region segmentation in generally. It can be allowed many face detection techniques to solve the first and second problems. However, it is not easy to detect a face divided into several parts of regions for reason of different illumination conditions in the third problem. Therefore, we propose an efficient modified skin segmentation algorithm to solve this problem because the typical region segmentation algorithm can not be used to. Our algorithm detects skin regions over the entire image, and then generates face candidate regions using our skin segmentation algorithm For each face candidate, we implement the procedure of region merging for divided regions in order to make a region using adjacency between homogeneous regions. We utilize various different searching window sizes to detect different size faces and a face detection classifier based on a back-propagation algorithm in order to verify whether the searching window contains a face or not.