• 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 Journal of Korean Institute of Communications and Information Sciences
• /
• v.38C no.8
• /
• pp.663-673
• /
• 2013

The drastic growth of mobile communication and spreading of smart phone make the significant attention on Location Based Service. The one of most important things for vitalization of LBS is the accurate estimating position for mobile object. Focusing on IMU deployed in smart phone, we develop a hybrid positioning estimation framework with a combination of WPS. The developed approaches can strengthen the advantages of independent indoor applicability of IMU. The estimation of IMU is efficiently compensated by radio fingerprint based Wi-Fi Positioning System. We put a focus especially on the hybrid algorithmic framework. Compared on the existing approaches of WPS or IMU, we achieve the comparable higher performance on both of average error of estimation and deviation of errors. Furthermore test-bed based on smart phone platform is practically developed and all data have been harvested from the actual measurement of test indoor area. This can approve the practical usefulness of proposed framework.

• Journal of Korean Society of Transportation
• /
• v.26 no.2
• /
• pp.89-100
• /
• 2008

In an urban network controlled by traffic signals, there is an interaction between the signal timing and the routes chosen by individual road users. This study develops a bi level programming model for traffic signal optimization in networks with path based traffic assignment. In the bi level programming model, genetic algorithm approach has been proposed to solve upper level problem for a signalized road network. Path based traffic assignment using column generation technique which is proposed by M.H. Xu, is applied at the lower-level. Genetic Algorithm provieds a feasible set of signal timings within specified lower and upper bounds signal timing variables and feeds into lower level problem. The performance of this model is investigated in numerical experiment in a sample network. In result, optimal signal settings and user equilibrium flows are made.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.35 no.2
• /
• pp.107-114
• /
• 2007

This paper focuses on the performance evaluation of various control allocation methods applied on DURUMI-II UAV system. In order to implement control allocation scheme to aircraft control system, control system can be designed through two step design procedure. The first step is to design a baseline control system for an aircraft without consideration of control surface failure. The second step is to design a control allocator that maps the total control command on the individual control surfaces. In this paper, several control allocation methods such as Psuedo-Inverse CA method, Direct CA method, and Optimization CA method are implemented and integrated to the baseline flight control system of DURUMI-II UAV. The performance of these control allocation methods is evaluated by nonlinear simulation under the flight scenario of control surface failure.

• Journal of KIISE:Software and Applications
• /
• v.29 no.3
• /
• pp.145-155
• /
• 2002

In content-based image retrieval (CBIR), most conventional approaches assume a linear relationship between different features and require users themselves to assign the appropriate weights to each feature. However, the linear relationship assumed between the features is too restricted to accurately represent high-level concepts and the intricacies of human perception. In this paper, a neural network-based image retrieval (NNIR) model is proposed. It has been developed based on a human-computer interaction approach to CBIR using a radial basis function network (RBFN). By using the RBFN, this approach determines the nonlinear relationship between features and it allows the user to select an initial query image and search incrementally the target images via relevance feedback so that more accurate similarity comparison between images can be supported. The experiment was performed to calculate the level of recall and precision based on a database that contains 1,015 images and consists of 145 classes. The experimental results showed that the recall and level of the proposed approach were 93.45% and 80.61% respectively, which is superior than precision the existing approaches such as the linearly combining approach, the rank-based method, and the backpropagation algorithm-based method.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.4
• /
• pp.959-968
• /
• 1999

several papers have reported that parallel heuristics or hybrid approaches combining several heuristics can get better results. However, the parallelization and hybridization of any search methods on the single CPU type computer need enormous computation time. that case, we need more elegant combination method. For this purpose, we propose Fast Model of Parallel Heuristics(FMPH). FMPH is based on the island model of parallel genetic algorithms and takes local search to the elite solution obtained form each island(sub group). In this paper we introduce how can we adapt FMPH to the job-shop scheduling problem notorious as the most difficult NP-hard problem and report the excellent results of several famous benchmark problems.

• Korean Journal of Remote Sensing
• /
• v.30 no.2
• /
• pp.251-258
• /
• 2014

We upgraded to utilize a novel method for combining the analog to digital converter and photon-counting measurements for backscatter photon signal of lidar. We have and improve the standard combining method for determination of those conversion factors between analog to digital converter data and photon-counting data measurement which is conducted dead time correction. The combining method and dead time correction method presented here has been successfully applied to experimental data obtained in Gwangju, Korea.

• The Korean Journal of Applied Statistics
• /
• v.13 no.2
• /
• pp.393-405
• /
• 2000

Box and Draper( 19(5) listed some properties of a design that should be considered in design selection. But it is impossible that one design criterion from optimal experimental design theory reflects many potential objectives of an experiment, because the theory was originally based on the underlying model and its strict assumption about the error structure. Therefore, when it is neces::;ary to implement multi-objective experimental design. it is common practice to balance out the several optimal design criteria so that each design criterion involved benefits in terms of its relative "high" efficiency. In this study, we proposed several composite design criteria taking the case of heteroscedastic model. WVhen the heteroscedasticity is present in the model. the well known equivalence theorem between 1)- and C-optimality no longer exists and furthermore their design characteristics are sometimes drastically different. We introduced three different design criteria for this purpose: constrained design, combined design, and minimax design criteria. While the first two methods do reflect the prior belief of experimenter, the last one does not take it into account. which is sometimes desirable. Also we extended this method to the case when there are uncertainties concerning the error structure in the model. A simple algorithm and concluslOn follow.On follow.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.44 no.3 s.357
• /
• pp.26-32
• /
• 2007

A simple but accurate equivalent circuit of an aperture-coupled cavity-fed microstrip patch antenna is developed. It consists of ideal transformers, admittance elements, and transmission lines, and the related circuit element values are computed by applying the reciprocity theorem and complex power concept with the spectral-domain immittance approach. After validating by the published design example, a dual-band antenna was designed with the help of a hybrid optimization method. For this purpose, the Genetic Algorithm is applied with the Nelder-Mead simplex method. The obtained good results show that this approach turned out to be a very efficient tool for the design of aperture-coupled cavity-fed microstrip patch antenna having various structural design parameters.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.8 no.6
• /
• pp.121-130
• /
• 2009

In this paper, Gaussian probability distribution model based multi-sensor data fusion algorithm is proposed for a vehicular location awareness system. Conventional vehicular location awareness systems are operated by GPS (Global Positioning System). However, the conventional system is not working in the indoor of building or urban area where the receiver is difficult to receive the signal from satellites. A method which is combined GPS and UWB (Ultra Wide-Band) has developed to improve this problem. However, vehicular is difficult to receive seamless location information since the measurement systems by both GPS and UWB convert the vehicle's movement information separately at each sensor. In this paper, normalized probability distribution model based Hybrid UWB/GPS is proposed by utilizing GPS location data and UWB sensor data. Therefore the proposed system provides information with seamless and location flexible properties. The proposed system tested by Ubisense and Asen GPS in the $12m{\times}8m$ outdoor environments. As a result, the proposed system has improved performance for accurateness and connection ability between devices to support various CNS (Car Navigation System).