• Journal of Korea Spatial Information System Society
• /
• v.5 no.1 s.9
• /
• pp.83-89
• /
• 2003

The GIS which is analysis of the real world to construction of 3D virtual city develop s in rapid growth. 3D virtual city is simulated by use of a GIS, Computer graphics, virtual reality and Spatial database. In this paper 3D topographical basemap which have the geographic coordinate of world was constructed by digital map. And build the Cyber city with combining the building that have elevation and 3D topographical basemap. By using server/client system for the cyber city. 3D cyber city web service implemented. We proposed the hybrid base web service method rather than the image or vector base web service. By the spatial and attribute search in the 3D Cyber City, overcome the existing simple visibility of Web 3D technology, and exhibited development direction to the Web 3D GIS.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.1
• /
• pp.270-279
• /
• 1997

The conversion of printed maps into computerized databases is an enormous task. Thus the automation of the conversion process is essential. Efficient computer representation of printed maps and line drawings depends on codes assigned to characters, symbols, and vector representation of the graphics. In many cases, maps are constructed in a number of layers, where each layer is printed in a distinct color, and it represents a subset of the map information. In order to properly represent the character layer from color map images, an interactive clustering and character extraction technique is proposed. Character is usually separated from graphics by extracting and classifying connected components in the image. But this procedure fails, when characters touch or overlap lines-something that occurs often in land register maps. By vectorizing line segments, the touched characters and numbers are extracted. The algorithm proposed in this paper is intended to contribute towards the solution of the color image clustering and touched character problem.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.10 no.8
• /
• pp.1502-1509
• /
• 2006

In this paper, we proposed reliability and capacity enhancement methods for IEEE 802.15.3 HDR-WPAN (High Data Rate-Wireless Personal Area Network) system which is currently getting an interest in home network technology adopting a MIMO technique. We also analyzed performance or the proposed system through a computer simulation. The HDR-WPAN system using V-BLAST algorithm, transmitting the different signal vector to each other's sub-channel, can get the transmission speed of more than 110Mbps using two Tx/Px antenna without bandwidth expansion in TCM-64QAM mode. Also the proposed system has reliability of 104 at $E_b/N_0=35dB$ under the Rayleigh fading channel in case of two Tx/Rx antenna with MMSE algorithm. The HDR-WPAN system adopting V-BLAST method has its drawback which is very complicated to determine the decision-ordering at the receiver. But, the proposed system enhances the transmission capacity and reliability without extra bandwidth expansion by sending data streams to multiple antennas.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.21 no.7
• /
• pp.1306-1312
• /
• 2017

The route request (RREQ) packet is selectively re-broadcasted in the routing protocols that improve the broadcast storm problem of the ad-hoc on-demand routing protocol (AODV). However, in a low node density scenario, the connectivity of these selective rebroadcast schemes becomes less than that of the AODV. In order to clarify the requirements of these selective re-broadcast routing protocols, it is necessary to investigate the relationship between the node density and the connectivity. In this paper, we drive a probability to preserve the connectivity of the GAODV at an intermediate rebroadcast node. In addition, we present an intuitive method to approximate the end-to-end connectivity of the GAODV. We draw the required node density to guarantee the connectivity of 0.9 and 0.99 through computer simulations, and verify the validity of the derived theoritical connectivity by comparing with the simulation results.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.6
• /
• pp.1477-1484
• /
• 2015

This paper proposes a robust method for object tracking based on Kalman filters algorithm and covariance matrix. As a feature of the object to be tracked, covariance matrix ensures the continuity of the moving target tracking in the image frames because the covariance is addressed spatial and statistical properties as well as the correlation properties of the features, despite the changes of the form and shape of the target. However, if object moves faster than operation time, real time tracking is difficult. In order to solve the problem, Kalman filters are used to estimate the area of the moving object and covariance matrices as a feature vector are compared with candidate regions within the estimated Kalman window. The results show that the tracking rate of 96.3% achieved using the proposed method.

• The KIPS Transactions:PartD
• /
• v.8D no.4
• /
• pp.305-312
• /
• 2001

Recently, high-dimensional index structures have been required for similarity search in such database applications s multimedia database and data warehousing. In this paper, we propose a new cell-based signature tree, called CS-tree, which supports efficient storage and retrieval on high-dimensional feature vectors. The proposed CS-tree partitions a high-dimensional feature space into a group of cells and represents a feature vector as its corresponding cell signature. By using cell signatures rather than real feature vectors, it is possible to reduce the height of our CS-tree, leading to efficient retrieval performance. In addition, we present a similarity search algorithm for efficiently pruning the search space based on cells. Finally, we compare the performance of our CS-tree with that of the X-tree being considered as an efficient high-dimensional index structure, in terms of insertion time, retrieval time for a k-nearest neighbor query, and storage overhead. It is shown from experimental results that our CS-tree is better on retrieval performance than the X-tree.

• The KIPS Transactions:PartC
• /
• v.14C no.2
• /
• pp.191-198
• /
• 2007

A mobile ad-hoc network (MANET) is an autonomous, infrastructure-less system that consists of mobile nodes. In MANET, on demand routing protocols are usually used because network topology changes frequently. AODV, which is a representative on demand routing protocol, operates using the routing table of each node that includes next hop of a route for forwarding packets. It maintains the established route if there is not an expiration of route or any link break. In the paper, we propose a partially adaptive route maintenance scheme (AODV-PA) based on AODV, which provides dynamic route modification of initial route for selecting the effective route using not only next hop but also next-hop of next-hop (i.e. 2-hop next node) acquired through route discovery process. In addition, the proposed scheme additionally manages the routing table for preventing exceptional link breaks by route modification using HELLO messages. We use NS 2 for the computer simulation and validate that the proposed scheme is better than general AODV in terms of packet delivery ratio, latency, routing overhead.

• Journal of Broadcast Engineering
• /
• v.18 no.1
• /
• pp.77-87
• /
• 2013

In this paper, we present a novel method for local image descriptor called exact order based descriptor (EOD) which is robust to illumination changes and Gaussian noise. Exact orders of image patch is induced by changing discrete intensity value into k-dimensional continuous vector to resolve the ambiguity of ordering for same intensity pixel value. EOD is generated from overall distribution of exact orders in the patch. The proposed local descriptor is compared with several state-of-the-art descriptors over a number of images. Experimental results show that the proposed method outperforms many state-of-the-art descriptors in the presence of illumination changes, blur and viewpoint change. Also, the proposed method can be used for many computer vision applications such as face recognition, texture recognition and image analysis.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.27 no.5
• /
• pp.383-392
• /
• 2007

In this paper, we study the prediction of depth and width of a defect in steam generator tube in nuclear power plant using neural network. To this end, we first generate eddy current testing (ECT) signals for 4 defect patterns of SG tube: I-In type, I-Out type, V-In type, and V-Out type. In particular, we generate 400 ECT signals for various widths and depths for each defect type by the numerical analysis program based on finite element modeling. From those generated ECT signals, we extract new feature vectors for the prediction of defect size, which include the angle between the two points where the maximum impedance and half the maximum impedance are achieved. Using the extracted feature vector, multi-layer perceptron with one hidden layer is used to predict the size of defects. Through the computer simulation study, it is shown that the proposed method achieves decent prediction performance in terms of maximum error and mean absolute percentage error (MAPE).

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.11 no.3
• /
• pp.229-234
• /
• 2018

Texture is one of the most useful features in classifying and segmenting images. The LBP-based approach previously presented in the literature has been successful in many applications. However, it's theoretical foundation is based only on the difference of pixel values, and consequently it has a number of drawbacks like it performs poorly for the images corrupted with noise, and especially it cannot be used as a multiscale texture descriptor due to the exploding increase of feature vector dimension with increase of the number of neighbor pixels. In this paper, we present a method to address these drawbacks of LBP-based approach. More specifically, our approach quantizes the range of pixels values and construct a 3D histogram which captures the correlative information of pixels. This histogram is used as a texture feature. Several tests with texture images show that the proposed method outperforms the LBP-based approach in the problem of texture classification.