• Journal of Internet Computing and Services
• /
• v.10 no.4
• /
• pp.13-23
• /
• 2009

In this paper we propose an approach for localizing objects in satellite images. Our method exploits matching features based on description vectors. We applied Scale Invariant Feature Transform (SIFT) to object localization. First, we find keypoints of the satellite images and the objects and generate description vectors of the keypoints. Next, we calculate the similarity between description vectors, and obtain matched keypoints. Finally, we weight the adjacent pixels to the keypoints and determine the location of the matched object. The experiments of object localization by using SIFT show good results on various scale and affine transformed images. In this paper the proposed methods use Google Earth satellite images.

• Journal of Korea Multimedia Society
• /
• v.24 no.3
• /
• pp.416-422
• /
• 2021

Due to the large differences in human activity within classes, the large similarity between classes, and the problems of visual angle and occlusion, it is difficult to extract features manually, and the detection rate of human behavior is low. In order to better solve these problems, an improved Faster R-CNN-based detection algorithm is proposed in this paper. It achieves multi-object recognition and localization through a second-order detection network, and replaces the original feature extraction module with Dense-Net, which can fuse multi-level feature information, increase network depth and avoid disappearance of network gradients. Meanwhile, the proposal merging strategy is improved with Soft-NMS, where an attenuation function is designed to replace the conventional NMS algorithm, thereby avoiding missed detection of adjacent or overlapping objects, and enhancing the network detection accuracy under multiple objects. During the experiment, the improved Faster R-CNN method in this article has 84.7% target detection result, which is improved compared to other methods, which proves that the target recognition method has significant advantages and potential.

• The KIPS Transactions:PartD
• /
• v.13D no.6 s.109
• /
• pp.789-796
• /
• 2006

Context-aware is the core in ubiquitous environment of sensor network to support intelligent and contextual adaptation service. The new context information model is demanded to support context-aware applications. The model should not depend on a specified application and be shareable between applications in the same environment. Also, it should support various context representation and complex context-aware. In this paper, we define the context information according to context-aware process. Also we design the knowledge of domain as well as applications using ontologies and rules. The domain spatial ontology and application knowledge are represented using the spatial object model and the rules of expanded ontologies, respectively. The expression of abundant spatial ontology represents the context information about distance between objects and adjacent object as well as the location of the object. The proposed context information model which is able to exhibit various spatial context and recognizes complex spatial context through the existing GIS. This model shows that it can adapt to a large scale outdoor context-aware applications such as air pollution and prevention of disasters as well as various context-aware applications.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.2 s.40
• /
• pp.25-33
• /
• 2006

We propose a method that automatically classifies the images into the object and non-object images. An object image is the image with object(s). An object in an image is defined as a set of regions that lie around center of the image and have significant color distribution against the other surround (or background) regions. We define four measures based on the characteristics of an object to classify the images. The center significance is calculated from the difference in color distribution between the center area and its surrounding region. Second measure is the variance of significantly correlated colors in the image plane. Significantly correlated colors are first defined as the colors of two adjacent pixels that appear more frequently around center of an image rather than at the background of the image. Third one is edge strength at the boundary of candidate for the object. By the way, it is computationally expensive to extract third value because central objects are extracted. So, we define fourth measure which is similar with third measure in characteristic. Fourth one can be calculated more fast but show less accuracy than third one. To classify the images we combine each measure by training the neural network and SYM. We compare classification accuracies of these two classifiers.

• Journal of the Society of Naval Architects of Korea
• /
• v.57 no.2
• /
• pp.114-123
• /
• 2020

A high-order potential-based panel method based on Green's theorem, with piecewise-linear dipole strength on triangular panels, is formulated for the analysis of potential flow around a three-dimensional wing. Previous low-order panel methods adopt square panels with piecewise-constant dipole strength, which results in inherent errors. Square panels can not represent a high curvature lifting body, such as propellers, since the four vertices of the square panel do not locate at the same flat plane. Moreover the piecewise-constant dipole strength induces inevitable errors due to the steps in dipole strength between adjacent panels. In this paper a high-order panel method is formulated to improve accuracy by adopting a piecewise linear dipole strength on triangular panels. Firstly, the square panels are replaced by triangular panels in order to increase the geometric accuracy in representing the shape of the object with large curvature. Next, the step difference of the dipole strength between adjacent panels is removed by adopting piecewise-linear dipole strength on the triangular panels. The calculated results by the present method is compared with analytical ones for simple non-lifting geometries, such as ellipsoid. The results for an elliptic wing with zero thickness at finite angle of attack are compared with Jordan's results. The comparison shows reasonable agrements for the both lifting and non-lifting bodies.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.21 no.3
• /
• pp.193-198
• /
• 2003

The population is increased in the area of a subway station because the accessibility of passengers is improved. Therefore, facilities for commercial purpose are concentrated in this area. To develop the station area as the center among the most urbanized area, overall mater plan should be constructed far the station area. This study was to construct web server for management a variety of 3D spatial object database of station areas using GIS and web 3D technology. These results will be used to manage efficiently a urban space by the connection of a subway station and a adjacent facilities.

• Geophysics and Geophysical Exploration
• /
• v.5 no.2
• /
• pp.93-98
• /
• 2002

A three dimensional model for the orebody of an operating mine in Korea was constructed by using a program called '3-D Modeler'. The program allows the user to interactively construct a 3-D model of an orebody from its horizontal cross-sections. The 3-D Modeler is easily able to combine and display various spatial data for model construction. The result of modeling is strongly influenced by control points that correlate to the adjacent horizontal cross-sections. The control points are determined by comparing the geometrical shape of the adjacent cross-sections in conjunction with the geological features of the orebody. The resulting model can be evaluated in viewing the constructed object in three dimensional space or more closely evaluated by inspecting the cross-section. The model can iteratively be improved by modifying the shape of the cross-section and by using this new cross-section for the model building.

• Journal of Electrical Engineering and Technology
• /
• v.11 no.4
• /
• pp.1003-1011
• /
• 2016

In this paper, a new algorithm by using 3D warping technique to effectively fill holes that are produced when creating a virtual-viewpoint image is proposed. A hole is defined as the region that cannot be seen in the reference view when a virtual view is created. In the proposed algorithm, to reduce the blurring effect that occurs on the hole region filled by conventional algorithms and to enhance the texture quality of the generated virtual view, Exemplar Based In-painting algorithm is used. The boundary noise which occurs in the initial virtual view obtained by 3D warping is also removed. After 3D warping, we estimate the relative location of the background to the holes and then pixels adjacent to the background are filled in priority to get better result by not using only adjacent object's information. Also, the temporal inconsistency between frames can be reduced by expanding the search region up to the previous frame when searching for most similar patch. The superiority of the proposed algorithm compared to the existing algorithms can be shown through the experimental results.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.11
• /
• pp.63-77
• /
• 1994

This paper describes the real-time system which, through analyzing a sequence of images, can extract motional information on a moving object and can contol servo equipment to always locate the moving object at the center of an image frame. An image is a vast amount of two-dimensional signal, so it takes a lot of time to analyze the whole quantity of a given image. Especially, the time needed to load pixels from a memory to processor increase exponentially as the size of an image increases. To solve such a problem and track a moving object in real-time, this paper addresses how to selectively search the spatial and time domain. Based on the selective search of spatial and time domain, this paper suggests various types of techniques which are essential in implementing a real-time tracking system. That is, this paper describes how to detect an entrance of a moving object in the field of view of a camera and the direction of the entrance, how to determine the time interval of adjacent images, how to determine nonstationary areas formed by a moving object and calculated velocity and position information of a moving object based on the determined areas, how to control servo equipment to locate the moving object at the center of an image frame, and how to properly adjust time interval(${\Delta}$t) to track an object taking variable speed.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_1
• /
• pp.535-543
• /
• 2022

A drone is used to diagnose crop growth and to provide information through images in the agriculture field. In the case of using high spatial resolution drone images, growth information for each object can be produced. However, accurate object detection is required and adjacent objects should be efficiently classified. The purpose of this study is to develop a Chinese cabbage object detection algorithm using multispectral reflectance images observed from drone and computer vision techniques. Drone images were captured between 7 and 15 days after planting a Chinese cabbage from 2018 to 2020 years. The thresholds of object detection algorithm were set based on 2019 year, and the algorithm was evaluated based on images in 2018 and 2019 years. The vegetation area was classified using the characteristics of spectral reflectance. Then, morphology techniques such as dilatation, erosion, and image segmentation by considering the size of the object were applied to improve the object detection accuracy in the vegetation area. The precision of the developed object detection algorithm was over 95.19%, and the recall and accuracy were over 95.4% and 93.68%, respectively. The F1-Score of the algorithm was over 0.967 for 2 years. The location information about the center of the Chinese cabbage object extracted using the developed algorithm will be used as data to provide decision-making information during the growing season of crops.