• Journal of Ocean Engineering and Technology
• /
• v.24 no.3
• /
• pp.64-71
• /
• 2010

This paper summarizes the development of an ART control system panel with a touch screen and sensors to measure the roll and roll rate of ships. The control system hardware consists of two micro-processors, analog and digital I/O circuits, various relay circuits, etc. Sensor fusion and moving cross algorithms are implemented to accurately estimate the roll angle and roll period. In addition, the control system adopts a fault detection algorithm to inform users of ART system faults. A touch screen in the control panel can display the ART system states and faults. The performance of the developed system was verified on real sea trials.

• Annual Conference of KIPS
• /
• 2015.10a
• /
• pp.1289-1291
• /
• 2015

본 논문에서는 충치 환자의 진단을 위해 구강 영상에서 충치를 추출하는 방법을 제안한다. 먼저 구강은 붉은색을 띄고 치아는 흰색을 띈다는 특징이 있기 때문에, 구강 영상을 YCbCr 컬러모델로 변환한다. YCbCr 컬러모델에 임계치를 설정하여 붉은 영역을 검출해내고, 검출된 붉은 영역에 대해 이진화하여 치아 영역을 추출한다. 그 후, 모폴로지 기법을 이용하여 잡음 제거 및 치아의 빈 공간을 채운다. 치아 영역 추출 시 영상에 따라 치아 사이를 잇는 모서리 부분이 손실된 경우가 발생할 수 있기 때문에 치아 사이의 손실된 부분을 연결 한다. 치아 영역에 ART2 알고리즘을 적용하여 클러스터링하고 충치 후보 영역을 추출한다. 충치 후보 영역에 8방향 윤곽선 추적 기법을 적용하여 충치를 분석 및 추출한다. 실험 결과 81%의 추출 성공률을 보였고 다양한 형태의 충치를 효과적으로 추출할 수 있는 것을 확인하였다.

• Current Optics and Photonics
• /
• v.5 no.6
• /
• pp.686-698
• /
• 2021

A camouflaged encryption scheme based on Hadamard matrix and ghost imaging is proposed. In the process of the encryption, an orthogonal matrix is used as the projection pattern of ghost imaging to improve the definition of the reconstructed images. The ciphertext of the secret image is constrained to the camouflaged image. The key of the camouflaged image is obtained by the method of sparse decomposition by principal component orthogonal basis and the constrained ciphertext. The information of the secret image is hidden into the information of the camouflaged image which can improve the security of the system. In the decryption process, the authorized user needs to extract the key of the secret image according to the obtained random sequences. The real encrypted information can be obtained. Otherwise, the obtained image is the camouflaged image. In order to verify the feasibility, security and robustness of the encryption system, binary images and gray-scale images are selected for simulation and experiment. The results show that the proposed encryption system simplifies the calculation process, and also improves the definition of the reconstructed images and the security of the encryption system.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.1
• /
• pp.363-372
• /
• 2017

This paper presents a novel face recognition algorithm based on the deep convolution neural network and key point detection jointed local binary pattern methodology to enhance the accuracy of face recognition. We firstly propose the modified face key feature point location detection method to enhance the traditional localization algorithm to better pre-process the original face images. We put forward the grey information and the color information with combination of a composite model of local information. Then, we optimize the multi-layer network structure deep learning algorithm using the Fisher criterion as reference to adjust the network structure more accurately. Furthermore, we modify the local binary pattern texture description operator and combine it with the neural network to overcome drawbacks that deep neural network could not learn to face image and the local characteristics. Simulation results demonstrate that the proposed algorithm obtains stronger robustness and feasibility compared with the other state-of-the-art algorithms. The proposed algorithm also provides the novel paradigm for the application of deep learning in the field of face recognition which sets the milestone for further research.

• Journal of IKEEE
• /
• v.23 no.4
• /
• pp.1415-1422
• /
• 2019

Background subtraction is the major task of computer vision and image processing to detect changes in video. The best performing background subtraction is computationally expensive that cannot be used in real time in a typical computing environment. The proposed algorithm improves the background subtraction algorithm of the widely used MOG with the image resizing algorithm. The proposed image resizing algorithm is designed to drastically reduce the amount of computation and to utilize local information, which is robust against noise such as camera movement. Experimental results of the proposed algorithm have a classification capability that is close to the state of the art background subtraction method and the processing speed is more than 10 times faster.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.2
• /
• pp.837-856
• /
• 2016

Underwater image enhancement has received considerable attention in last decades, due to the nature of poor visibility and low contrast of underwater images. In this paper, we propose a new automatic underwater image enhancement algorithm, which combines nonsubsampled contourlet transform (NSCT) domain enhancement techniques with the mechanism of the human visual system (HVS). We apply the multiscale retinex algorithm based on the HVS into NSCT domain in order to eliminate the non-uniform illumination, and adopt the threshold denoising technique to suppress underwater noise. Our proposed algorithm incorporates the luminance masking and contrast masking characteristics of the HVS into NSCT domain to yield the new HVS-based NSCT. Moreover, we define two nonlinear mapping functions. The first one is used to manipulate the HVS-based NSCT contrast coefficients to enhance the edges. The second one is a gain function which modifies the lowpass subband coefficients to adjust the global dynamic range. As a result, our algorithm can achieve contrast enhancement, image denoising and edge sharpening automatically and simultaneously. Experimental results illustrate that our proposed algorithm has better enhancement performance than state-of-the-art algorithms both in subjective evaluation and quantitative assessment. In addition, our algorithm can automatically achieve underwater image enhancement without any parameter tuning.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.19 no.5
• /
• pp.1374-1405
• /
• 2025

This study proposes an enhanced version of the Subtraction Average-Based Optimizer (SABO) to address the slow convergence, local optima, and imbalance between exploration and exploitation inherent in the original algorithm. The enhancement incorporates chaotic mapping for uniform population initialization and introduces a sinusoidal function to enhance global search efficiency. The enhanced SABO algorithm is evaluated using 23 benchmark functions from IEEE CEC2005, and it outperforms several state-of-the-art algorithms in terms of convergence speed and accuracy. Compared to existing swarm intelligence algorithms, the enhanced SABO algorithm consistently demonstrates superior performance across all 23 benchmark functions. The practical applicability of the enhanced SABO algorithm is further validated through its application to a real-world engineering design problem. Experimental and statistical analyses confirm that the enhanced SABO algorithm achieves rapid convergence, demonstrates superior optimization capability, and exhibits strong effectiveness in addressing complex multimodal functions. Furthermore, the enhanced SABO algorithm effectively maintains a balance between exploration and exploitation, significantly enhancing solution quality in multi-objective optimization problems.

• Proceedings of the Korean Information Science Society Conference
• /
• 2002.04a
• /
• pp.676-678
• /
• 2002

In this work, we present the novel scheduling algorithm of the multimedia data retrieval for the mobile disk drive. Our algorithm is focused on minimizing the power consumption involved in data retrieval from the local disk drive. The prime commodity in mobile devices is the electricity. Strict restriction on power consumption requirement of the mobile device put unique demand in designing of its hardware and software components. State of the art disk based storage subsystem becomes small enough to be embedded in handhold devices. It delivers abundant storage capacity and portability. However, it is never be trivial to integrate small hard disk or optical disk drive in handhold devices due to its excessive power consumption. Our algorithm ARM in this article generates the optimal schedule of retrieving data blocks from the mobile disk drive while guaranteeing continuous playback of multimedia data.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.3
• /
• pp.514-518
• /
• 2007

It is necessary to modify the state-of-the-art of speed control theory because of the phase asymmetry in the Linear Induction Motor (LIM)and for the constant speed control of mover using single vector control inverter system, it is important that primary stack is located in appropriated intervals in the 3D conveyer system using LIM. The dynamic characteristic analysis method of the vector controlled LIM using coupled FEM and control algorithm taking into account the movement is proposed. The focus of this paper is the analysis relative to selecting primary stack intervals in order to constant speed control in the 3D conveyer system using LIM.

• Advances in Computational Design
• /
• v.1 no.1
• /
• pp.79-86
• /
• 2016

In this study, the three different meta-heuristics namely the Grey Wolf Optimizer (GWO), Stochastic Fractal Search (SFS), and Adaptive Differential Evolution with Optional External Archive (JADE) algorithms are examined. This study considers optimization of the planer frame to minimize its weight subjected to the strength and displacement constraints as per the American Institute of Steel and Construction - Load and Resistance Factor Design (AISC-LRFD). The GWO algorithm is associated with grey wolves' activities in the social hierarchy. The SFS algorithm works on the natural phenomenon of growth. JADE on the other hand is a powerful self-adaptive version of a differential evolution algorithm. A one-bay ten-story planar steel frame problem is examined in the present work to investigate the design ability of the proposed algorithms. The frame design is produced by optimizing the W-shaped cross sections of beam and column members as per AISC-LRFD standard steel sections. The results of the algorithms are compared. In addition, these results are also mapped with other state-of-art algorithms.