배경 구축 기법과 형태학적 연산 기반의 다중 선박 객체 검출 (original) (raw)
Related papers
배경잡음에 적응하는 진동센서 기반 목표물 탐지 알고리즘
Journal of the Institute of Electronics Engineers of Korea, 2013
We propose adaptive detection algorithm to reduce a false alarm by considering the characteristics of the random noise on the detection system based on a seismic sensor. The proposed algorithm consists of the first step detection using kernel function and the second step detection using detection classes. Kernel function of the first step detection is obtained from the threshold of the Neyman-Pearon decision criterion using the probability density functions varied along the noise from the measured signal. The second step detector consists of 4 step detection class by calculating the occupancy time of the footstep using the frist detected samples. In order to verify performance of the proposed algorithm, the detection of the footsteps using measured signal of targets (walking and running) are performed experimentally. The detection results are compared with a fixed threshold detector. The frist step detection result has the high detection performance of 95% up to 10m area. Also, the false alarm probability is decreased from 40% to 20% when it is compared with the fixed threshold detector. By applying the detection class(second step detector), it is greatly reduced to less than 4%.
Journal of the Society of Naval Architects of Korea, 2008
The design process becomes more difficult due to the increasing complexity of products. Thus, without any proper design experience, designer cannot handle his design problems systematically. Besides, the conventional optimal design method cannot be used effectively at the early design stage, since most design problems must be formulated in terms of objective and constraint functions based on the mathematical concepts of Operation Research. Thus, in this paper, new design concept based on FBS (Function-Behavior-Structure) design model is introduced to help the novice designer formulate the complex design problems systematically into a mathematical form. In this FBS model, function means the designer's new intents designer wants to create for, structure stand for a final product configuration and behaviour is a product's performance. FBS design model is thus rather totally different concept used for formulating design problem, compared with conventional optimal design method. To validate this new FBS model, 330K VLCC design case is performed, and we found, though it is one design example case, that this new design concept could be effectively used for future ship design problems since, during the formulating design problem, the only engineering terminology such as function, structure, and behaviour of design product is used based on the engineering concepts, instead of mathematical terminology such as objective and constraints.
Journal of the Institute of Electronics Engineers of Korea, 2013
In this paper, we propose a complex-valued support vector machine (SVM) classifier which process the complex valued signal measured by pulse doppler radar (PDR) to identify moving targets from the background. SVM is widely applied in the field of pattern recognition, but features which used to classify are almost real valued data. Proposed complex-valued SVM can classify the moving target using real valued data, imaginary valued data, and cross-information data. To design complex-valued SVM, we consider slack variables of real and complex axis, and use the KKT (Karush-Kuhn-Tucker) conditions for complex data. Also we apply radial basis function (RBF) as a kernel function which use a distance of complex values. To evaluate the performance of the complex-valued SVM, complex valued data from PDR were classified using real-valued SVM and complex-valued SVM. The proposed complex-valued SVM classification was improved compared to real-valued SVM for dog and human, respectively , , have been improved.
베이즈 분류기를 이용한 수중 배경소음하의 과도신호 분류
Journal of Ocean Engineering and Technology, 2012
In this paper, a Bayesian classifier based on PCA (principle component analysis) is proposed to classify underwater transient signals using 16 th order LPC (linear predictive coding) coefficients as feature vector. The proposed classifier is composed of two steps. The mechanical signals were separated from biological signals in the first step, and then each type of the mechanical signal was recognized in the second step. Three biological transient signals and two mechanical signals were used to conduct experiments. The classification ratios for the feature vectors of biological signals and mechanical signals were 94.75% and 97.23%, respectively, when all 16 order LPC vector were used. In order to determine the effect of underwater noise on the classification performance, underwater ambient noise was added to the test signals and the classification ratio according to SNR (signal-to-noise ratio) was compared by changing dimension of feature vector using PCA. The classification ratios of the biological and mechanical signals under ocean ambient noise at 10dB SNR, were 0.51% and 100% respectively. However, the ratios were changed to 53.07% and 83.14% when the dimension of feature vector was converted to three by applying PCA. For correct, classification, it is required SNR over 10 dB for three dimension feature vector and over 30dB SNR for seven dimension feature vector under ocean ambient noise environment.
Matching Simulations with Tests of Cruise Bus Using Multi-body Dynamics Technology
2010
In this study, a large bus is tested for measuring the steering response based on the slarom test and step steer test. A full car model by using ADAMS/Car is established for computer simulation. For bus modeling, user defined templates are made and used in the simulation. Simulation results according to the slarom and step steer test are compared to the physical experiments, in which several sensors are installed to measure vehicle responses. The results obtained from the comparison show a good agreement with regard to the vehicle velocity and steering angle.
Journal of the Society of Naval Architects of Korea, 2021
Korean coastal fishery suffers from profitability degradation due to a decrease in fisheries resources, pollution in coastal waters, fuel coast increase, and market opening for aquaculture products. The next generation Korean fishing vessel aims at the improvement of energy efficiency, enhancement of crew welfare, and safety. These purposes can be accomplished by adopting a new standard hull form with improved resistance performance and a modernized residence facility on the deck. In order to improve resistance performance, this study attempts to optimize design variables for stern flaps for three kinds of fishing vesselscoastal multipurpose , coastal trap, and dredged nets. A series of model tests for these fishing vessels was carried out in the towing tank of Pusan National University. The results indicate that for some cases, the stern flap caused the stern trim of the vessel to decrease, leading to the resistance reduction.
신경망 모델 기반 조선소 조립공장 작업상태 판별 알고리즘
IE interfaces, 2011
In the shipbuilding industry, since production processes are so complicated that the data collection for decision making cannot be fully automated, most of production planning and controls are based on the information provided only by field workers. Therefore, without sufficient information it is very difficult to manage the whole production process efficiently. Job status is one of the most important information used for evaluating the remaining processing time in production control, specifically, in block assembly shop. Currently, it is checked by a production manager manually and production planning is modified based on that information, which might cause a delay in production control, resulting in performance degradation. Motivated by these remarks, in this paper we propose an efficient algorithm for identifying job status in block assembly shop for shipbuilding. The algorithm is based on the multi-layer perceptron neural network model using two key factors for input parameters. We showed the superiority of the algorithm by using a numerical experiment, based on real data collected from block assembly shop.
Journal of the Institute of Electronics Engineers of Korea, 2013
In this paper, we propose an algorithm for estimating media characteristics of sea water and subbottom multi-layers. The proposed algorithm for estimating reflection coefficients, uses a transmitted signal and reflected signal obtained from multiple layers of various shape and structure, and the algorithm is called Schur algorithm. The algorithm is efficient in estimating the reflection coefficients since it finds solution by converting the given inverse scattering problem into matrix factorization. To verify the proposed algorithm, we generate a transmit signal and reflected signal obtained from lattice filter model for sea water and subbottom of multi-level non-homogeneous layers, and then find that the proposed algorithm can estimate reflection coefficients efficiently.
Loading Preview
Sorry, preview is currently unavailable. You can download the paper by clicking the button above.