• Smart Structures and Systems
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• v.22 no.3
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• pp.315-326
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• 2018

This paper presents a novel time-domain method for the identification of plastic rotations and stiffness parameters of single-bay frames with nonlinear plastic hinges. Each plastic hinge is modelled as a pseudo-semi-rigid connection with nonlinear hysteretic moment-curvature characteristics at an element end. Through the comparison of the identified end rotations of members that are connected together, the plastic rotation that furnishes information of the locations and plasticity degrees of plastic hinges can be identified. The force consideration of the frame members may be used to relate the stiffness parameters to the elastic rotations and the excitation. The damped-least-squares method and damped-and-weighted-least-squares method are adopted to estimate the stiffness parameters of frames. A noise-removal strategy employing a de-noising technique based on wavelet packets with a smoothing process is used to filter out the noise for the parameter estimation. The numerical examples show that the proposed method can identify the plastic rotations and the stiffness parameters using measurements with reasonable level of noise. The unknown excitation can also be estimated with acceptable accuracy. The advantages and disadvantages of both parameter estimation methods are discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10C
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• pp.948-955
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• 2006

In this paper, we propose motion estimation and compensation using Low-Band-Shift(LBS) with Integer Lifting Shift property. To overcome shift-variant property on wavelet coefficients, the LBS was previously proposed. This method which is applied to reference frame in video coding technique has superior performance in terms of rate-distortion characteristic. However, this method needs more memory and computational complexity. For the enhancement of those disadvantages, we propose motion estimation using Low-Band-Shift with Integer Lifting. The Integer Lifting implementation gives us good efficiency of calculation and storage.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1C
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• pp.48-55
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• 2009

In scalable video coding, MCTF plays an important role for time-scalability and SNR-scalability. But there is image quality decreasing as MCTF level is increased because time interval of each frame is extended so that is hard to find suitable motion vector. In this paper, we propose an algorithm to prevent image quality from decreasing with unsuitable motion vector during MCTF update process using JND. We adapt JND to find errors within blocks of image and set a threshold which is used to add high frequency components during update process. We can overcome time-gap between frames and achieve better image quality through the proposed algorithm.

• Journal of IKEEE
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• v.24 no.4
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• pp.1148-1155
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• 2020

Fire must be extinguished as quickly as possible because they cause a lot of economic loss and take away precious human lives. Especially, the detection of smoke, which tends to be found first in fire, is of great importance. Smoke detection based on image has many difficulties in algorithm research due to the irregular shape of smoke. In this study, we introduce a new real-time smoke detection algorithm that reduces the detection of false positives generated by irregular smoke shape based on faster r-cnn of factory-installed surveillance cameras. First, we compute the global frame similarity and mean squared error (MSE) to detect the movement of smoke from the input surveillance camera. Second, we use deep learning algorithm (Faster r-cnn) to extract deferred candidate regions. Third, the extracted candidate areas for acting are finally determined using space and temporal features as smoke area. In this study, we proposed a new algorithm using the space and temporal features of global and local frames, which are well-proposed object information, to reduce false positives based on deep learning techniques. The experimental results confirmed that the proposed algorithm has excellent performance by reducing false positives of about 99.0% while maintaining smoke detection performance.

• Structural Engineering and Mechanics
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• v.82 no.3
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• pp.325-341
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• 2022

Previous major earthquakes indicated that the earthquake induced ground motions are typical non-stationary processes, which are non-stationary in both amplification and frequency. For the convenience of aseismic design and analysis, it usually assumes that the ground motions at structural supports are stationary processes. The development of time-frequency analysis technique makes it possible to evaluate the non-stationary responses of engineering structures subjected to non-stationary inputs, which is more general and realistic than the analysis method commonly used in engineering. In this paper, the wavelet-based stochastic vibration analysis methodology is adopted to calculate the non-stationary responses of multi-support structures. For comparison, the stationary response based on the standard random vibration method is also investigated. A frame structure and a two-span bridge are analyzed. The effects of non-stationary spatial ground motion and local site conditions are considered, and the influence of structural property on the structural responses are also considered. The analytical results demonstrate that the non-stationary spatial ground motions have significant influence on the response of multi-support structures.

• ETRI Journal
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• v.46 no.4
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• pp.671-682
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• 2024

Violence can be committed anywhere, even in crowded places. It is hence necessary to monitor human activities for public safety. Surveillance cameras can monitor surrounding activities but require human assistance to continuously monitor every incident. Automatic violence detection is needed for early warning and fast response. However, such automation is still challenging because of low video resolution and blind spots. This paper uses ResNet50v2 and the gated recurrent unit (GRU) algorithm to detect violence in the Movies, Hockey, and Crowd video datasets. Spatial features were extracted from each frame sequence of the video using a pretrained model from ResNet50V2, which was then classified using the optimal trained model on the GRU architecture. The experimental results were then compared with wavelet feature extraction methods and classification models, such as the convolutional neural network and long short-term memory. The results show that the proposed combination of ResNet50V2 and GRU is robust and delivers the best performance in terms of accuracy, recall, precision, and F1-score. The use of ResNet50V2 for feature extraction can improve model performance.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1427-1438
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• 2007

Video watermarking technologies are classified into types of four kinds. The first type is to embed the watermark into a raw video signal and to code the watermarked video signal. Most of video watermarking technologies fall into the category of this type. The second type is to apply watermarking to the coding process, such as block DCT and quantization. The third is to directly embed the watermark into the compressed bitstream itself. Generally, it is referred as labelling rather than watermarking. Finally, the fourth is to embed the water mark into MPEG motion vector. This type has the difficulty in real-time process because of the high complexity and has the blocking effects because of DCT-based on coder. In this paper, we proposed the digital video watermarking that embed the watermark in SPIHT video code for I-frame using motion vector analysis. This method can remove the blocking effect occurred at the DCT-based on coder and obtain video data that has progressive transmission property. The proposed method is to select the region for the watermark embedding in I frame using motion vector estimated from the previous P or B frame. And then, it is to perform DWT and embed the watermark based on HVS into the wavelet coefficients in the same subband of DWT as the motion vector direction. Finally, the watermarked video bitstream is obtained by the SPIHT coder. The experimental results verified that the proposed method has the invisibility from the objective and subjective image quality and the robustness against the various SPIHT compression and MPEG re-code.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1187-1193
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• 2014

This paper presents an effective motion estimation to improve the performance of the motion compensated temporal filtering (MCTF) which is a core part of the wavelet-based scalable video coding. The proposed scheme makes the motion vector field uniform by the modified median operation and the search strategies using adjacent motion vectors, in order to enhance the pixel connectivity which is significantly relevant to the performance of the MCTF. Moreover, the motion estimation with variable block sizes that reflects the features of frames is introduced for further correlation improvement of the motion vector field. Experimental results illustrate that the proposed method reduces the decomposed energy on the temporal high frequency subband frame up to 30.33% in terms of variance compared to the case of the full search with fixed block sizes.

• The Transactions of the Korea Information Processing Society
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• v.5 no.9
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• pp.2294-2301
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• 1998

The aim of this paper is to extract features from each news scenes for example, symbol icon which can be distinct each broadcasting corp, icon and caption which are has feature and important information for the scene in respectively, In this paper, we propose extraction methods of caption that has important prohlem of news videos and it can be classified in three steps, First of al!, we converted that input images from video frame to YIQ color vector in first stage. And then, we divide input image into regions in clear hy using equalized color histogram of input image, In last, we extracts caption using edge histogram based on vertical and horizontal line, We also propose the method which can extract news icon in selected key frames by the difference of inter-histogram and can divide each scene by the extracted icon. In this paper, we used comparison method of edge histogram instead of complex methcxls based on color histogram or wavelet or moving objects, so we shorten computation through using simpler algorithm. and we shown good result of feature's extraction.

• The Journal of the Korea Contents Association
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• v.9 no.5
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• pp.76-83
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• 2009

This paper presents a compression method for animated meshes or mesh sequences which have a shared connectivity and geometry streams. Our approach is based on static semi-regular mesh compression algorithm introduced by Khodakovky et al. Our encoding algorithm consists of two stages. First, the proposed technique creates a semi-regular mesh sequence from an input irregular mesh sequence. For semi-regular remeshing of irregular mesh sequences, this paper adapts the MAPS algorithm. However, MAPS cannot directly be performed to the input irregular mesh sequence. Thus, the proposed remesh algorithm revises the MAPS remesher using the clustering information, which classify coherent parts during the animation. The second stage uses wavelet transformation and clustering information to compress geometries of mesh sequences efficiently. The proposed compression algorithm predicts the vertex trajectories using the clustering information and the cluster transformation during the animation and compress the difference other frames from the reference frame in order to reduce the range of 3D position values.