• Proceedings of the KSRS Conference
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• v.2
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• pp.899-902
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• 2006

For a quick and accurate 3D modelling of a building, laser scanning data, digital maps, aerial photographs and satellite images should be fusioned. Moreover, library establishment according to a standard structure of a building and effective texturing method are required in order to determine the structure of a building. In this study, we made a standard library by categorizing Korean village forms and presented a model that can predict a structure of a building from a shape of the roof on an aerial photo image. We made an ortho image using the high-definition digital image and considerable amount of ground scanning point cloud and mapped this image. These methods enabled a more quick and accurate building modelling.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3217-3238
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• 2018

In this paper, a depth image up-sampling method is put forward by using pixel classifying and jointed bilateral filtering. By analyzing the edge maps originated from the high-resolution color image and low-resolution depth map respectively, pixels in up-sampled depth maps can be classified into four categories: edge points, edge-neighbor points, texture points and smooth points. First, joint bilateral up-sampling (JBU) method is used to generate an initial up-sampling depth image. Then, for each pixel category, different refinement methods are employed to modify the initial up-sampling depth image. Experimental results show that the proposed algorithm can reduce the blurring artifact with lower bad pixel rate (BPR).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.1064-1079
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• 2019

Information security has become increasingly important with the rapid development of mobile devices and internet. An efficient encryption system is a key to this end. In this paper, we propose an image encryption method based on the cross diffusion of two chaotic maps. We use two chaotic sequences, namely the Logistic map and the Chebyshev map, for key generation which has larger security key space than single one. Moreover, we use these two sequences for further image encryption diffusion which decreases the correlation of neighboring pixels significantly. We conduct extensive experiments on several well-known images like Lena, Baboon, Koala, etc. Experimental results show that our algorithm has the characteristics of large key space, fast, robust to statistic attack, etc.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.166-171
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• 2023

With significant advancements in the field of artificial intelligence, many novel algorithms and technologies have emerged. Currently, AI painting can generate high-quality images based on textual descriptions. However, it is often challenging to control details when generating images, even with complex textual inputs. Therefore, there is a need to implement additional control mechanisms beyond textual descriptions. Based on ControlNet, this passage describes a combined utilization of various local controls (such as edge maps and depth maps) and global control within a single model. It provides a comprehensive exposition of the fundamental concepts of ControlNet, elucidating its theoretical foundation and relevant technological features. Furthermore, combining methods and applications, understanding the technical characteristics involves analyzing distinct advantages and image differences. This further explores insights into the development of image generation patterns.

• Bulletin of the Korean Mathematical Society
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• v.42 no.1
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• pp.157-164
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• 2005

Let $RRat_k$ ($CP^n$) denote the space of basepoint-preserving conjugation-equivariant holomorphic maps of degree k from $S^2$ to $CP^n$. A map f ; $S^2 {\to}CP^n$ is said to be full if its image does not lie in any proper projective subspace of $CP^n$. Let $RF_k(CP^n)$ denote the subspace of $RRat_k(CP^n)$ consisting offull maps. In this paper we determine $H{\ast}(RF_k(CP^2); Z/p)$ for all primes p.

• Bulletin of the Korean Mathematical Society
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• v.41 no.3
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• pp.521-540
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• 2004

In this paper, we give a sharp estimate on the cardinality of the set generating the convex hull containing the image of harmonic maps with polynomial growth rate on a certain class of manifolds into a Cartan-Hadamard manifold with sectional curvature bounded by two negative constants. We also describe the asymptotic behavior of harmonic maps on a complete Riemannian manifold into a regular ball in terms of massive subsets, in the case when the space of bounded harmonic functions on the manifold is finite dimensional.

• Journal of the Korean Mathematical Society
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• v.42 no.3
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• pp.543-553
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• 2005

In this paper, we prove the existence of nonconstant bounded harmonic maps on a Cartan-Hadamard manifold of pinched negative curvature by solving the asymptotic Dirichlet problem. To be precise, given any continuous data f on the boundary at infinity with image within a ball in the normal range, we prove that there exists a unique harmonic map from the manifold into the ball with boundary value f.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.185-187
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• 2018

This paper presents an aircraft detection on panchromatic image using densely connected convolutional network. This algorithm connects all preceding feature-maps to all subsequent layers. It is encouraged to reuse feature-maps and enhance feature-maps representation. This algorithm is driven to learn aircraft feature to detect aircraft objects on panchromatic imagery. Based on the experimental result, it can yield accuracy of 92%.

• Journal of Korea Multimedia Society
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• v.19 no.12
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• pp.1909-1918
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• 2016

This paper presents a unified framework for joint Convolutional Neural Network (CNN) based vehicle detection by leveraging multi-spectral image pairs. With the observation that under challenging environments such as night vision and limited light source, vehicle detection in a single color image can be more tractable by using additional far-infrared (FIR) image, we design joint CNN architecture for both RGB and FIR image pairs. We assume that a score map from joint CNN applied to overall image can be considered as confidence of vehicle existence. To deal with various scale ratios of vehicle candidates, multi-scale images are first generated scaling an image according to possible scale ratio of vehicles. The vehicle candidates are then detected on local maximal on each score maps. The generation of overlapped candidates is prevented with non-maximal suppression on multi-scale score maps. The experimental results show that our framework have superior performance than conventional methods with a joint framework of multi-spectral image pairs reducing false positive generated by conventional vehicle detection framework using only single color image.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.303-309
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• 2008

Landcover map can use to establish basic national environment policy as main data predicting living place, counting pollution like a atmosphere, water and forest part. During the 1998-2005 years, Korean government made landcover maps using satellite image for part of south Korea. Landcover maps are offered free for public purpose to university and institute. So, it used basic data for policy and research parts. There are some problems for application parts because of inconsistency. So, in this study, to estimate accuracy of source data by quality checking for landcover maps. As a result, there are some errors like classification inconsistencies. So, it need verification process for landcover maps.