• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4092-4107
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• 2015

We propose a background subtraction method for moving cameras based on trajectory classification, image segmentation and label inference. In the trajectory classification process, PCA-based outlier detection strategy is used to remove the outliers in the foreground trajectories. Combining optical flow trajectory with watershed algorithm, we propose a trajectory-controlled watershed segmentation algorithm which effectively improves the edge-preserving performance and prevents the over-smooth problem. Finally, label inference based on Markov Random field is conducted for labeling the unlabeled pixels. Experimental results on the motionseg database demonstrate the promising performance of the proposed approach compared with other competing methods.

• Journal of Korea Multimedia Society
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• v.3 no.2
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• pp.184-191
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• 2000

In thid paper, we have analized the characteristics of $\Delta$-shaped filter based on preceeding study. The algorithm of $\Delta$-shaped filter for full screen display has been discussed including their edge-preserving characteristics and computaion complexity compared with the conventional algorithms. PSNR has been employed to compare the proposed method to the conventional algorithms. The proposed algorithm has been implemented using Synopsys VHDL tool. In addition, the features and trade off of the $\Delta$-shaped filter have been discussed.

• Journal of Korean Foot and Ankle Society
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• v.26 no.4
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• pp.157-162
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• 2022

Total ankle arthroplasty has become a viable motion-preserving alternative to ankle arthrodesis, especially in the last two decades. Recent improvements have been achieved in the strength of implant design and surgical technique. Nevertheless, addressing preoperative deformities is essential for successful outcomes of total ankle arthroplasty. Residual malalignment can produce instability and edge loading, causing acceleration of polyethylene wear, followed by osteolysis and an increased risk of revision surgery. Therefore, the accompanying deformities and their correction techniques need to be comprehensively elucidated and understood. In this article, we provide a review of the application of total ankle arthroplasty in arthritis with coronal plane varus and valgus deformities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1234-1257
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• 2023

In this paper, we propose a framework for multi-focus image fusion called PATN. In our approach, by aggregating deep features extracted based on the U-type Transformer mechanism and shallow features extracted using the PSA module, we make PATN feed both long-range image texture information and focus on local detail information of the image. Meanwhile, the edge-preserving information value of the fused image is enhanced using a dense residual block containing the Sobel gradient operator, and three loss functions are introduced to retain more source image texture information. PATN is compared with 17 more advanced MFIF methods on three datasets to verify the effectiveness and robustness of PATN.

• Structural Engineering and Mechanics
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• v.92 no.1
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• pp.65-79
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• 2024

This work aims to present an analysis of the structural reliability of reinforced concrete (RC) columns designed according to the general method outlined in Eurocode 2 (EN 1992-1-1 2004). Probabilistic analyses are conducted by integrating the Monte Carlo method with metamodels (or surrogate models) generated using Kriging and some machine learning techniques. The study was developed based on an algorithm that verifies the columns subject to biaxial bending, considering the physical and geometric nonlinearities. Columns were analyzed assuming sign inversion of end bending moments (with reverse curvature), which portray the typical situations in conventional structures of RC buildings. The probabilistic results reveal that the typical RC columns in buildings designed according to the design procedures of the studied standard, whether they are located at the center, corner, or edge, exhibit reliability levels surpassing those deemed acceptable within the technical community. Furthermore, the integration of surrogate models proves beneficial by alleviating the computational burden associated with evaluations while preserving accuracy.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.1_2
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• pp.59-66
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• 2004

In this paper, a fast 3D model extraction algorithm with an enhanced PBIL of preserving depth consistency is proposed for the extraction of 3D depth information from 2D images. Evolutionary computation algorithms are efficient search methods based on natural selection and population genetics. 2D disparity maps acquired by conventional matching algorithms do not match well with the original image profile in disparity edge regions because of the loss of fine and precise information in the regions. Therefore, in order to decrease the imprecision of disparity values and increase the quality of matching, a compact genetic algorithm is adapted for matching environments, and the adaptive window, which is controlled by the complexity of neighbor disparities in an abrupt disparity point is used. As the result, the proposed algorithm showed more correct and precise disparities were obtained than those by conventional matching methods with relaxation scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1844-1850
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• 2016

The bilateral filter can reduce the noise while preserving details computing the filtering output at each pixels as the average of neighboring pixels. In this paper, we propose a real-time system based on window division. Overall performance is increased due to the parallel architectures which computes five rows in the kernel window simultaneously but with pipelined scheduling. We consider the tradeoff between the filter performance and the hardware cost and the bit allocation has been determined by PSNR analysis. The proposed architecture is designed with verilogHDL and synthesized using Dongbu Hitek 110nm standard cell library. The proposed architecture shows 416Mpixels/s (397fps) of throughput at 416MHz of operating frequency with 132K gates.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.449-460
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• 2020

Super-resolution is a technique used to reconstruct an image with low-resolution into that of high-resolution. Recently, deep-learning based super resolution has become the mainstream, and applications of these methods are widely used in the remote sensing field. In this paper, we propose a super-resolution method based on the deep back-projection network model to improve the satellite image resolution by the factor of four. In the process, we customized the loss function with the edge loss to result in a more detailed feature of the boundary of each object and to improve the stability of the model training using generative adversarial network based on Wasserstein distance loss. Also, we have applied the detail preserving image down-scaling method to enhance the naturalness of the training output. Finally, by including the modified-residual learning with a panchromatic feature in the final step of the training process. Our proposed method is able to reconstruct fine features and high frequency information. Comparing the results of our method with that of the others, we propose that the super-resolution method improves the sharpness and the clarity of WorldView-3 and KOMPSAT-2 images.

• Journal of Korean Society for Geospatial Information Science
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• v.4 no.1 s.6
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• pp.93-102
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• 1996

For an atomatic generation of DEM(Digital Elevation Model) by computer, it is a time-consumed work to determine adquate matches from stereo images. Correlation and evenly distributed area-based method is generally used for matching operation. In this paper, we propose a new approach that computes matches efficiantly by changing the size of mask window and search area according to the given terrain information. For image segmentation, at first edge-preserving smoothing filter is used for preprocessing, and then region growing algorithm is applied for the filterd images. The segmented regions are classifed into mountain, plain and water area by using MRF(Markov Random Filed) model. Maching is composed of predicting parallex and fine matching. Predicted parallex determines the location of search area in fine matching stage. The size of search area and mask window is determined by terrain information for each pixel. The execution time of matching is reduced by lessening the size of search area in the case of plain and water. For the experiments, four images which are covered $10km{\times}10km(1024{\times}1024\;pixel)$ of Taejeon-Kumsan in each are studied. The result of this study shows that the computing time of the proposed method using terrain information for matching operation can be reduced from 25% to 35%.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.56-63
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• 2012

In this paper, adaptive unsharp masking using bilateral filter, edge-preserving smoothing filter is proposed to reduce the overshoot and jagging artifact in sharpening images. Previous image enhancement methods including unsharp masking(UM) can emphasize high-frequency details strongly, but often cause several artifacts such as overshooting, noise, jagging and so on. Proposed image enhancement method preserves edges well because of using bilateral filter and sensitively controls a weight according to edge's directions. Therefore, it enhances sharpness and effectively reduces overshoot and jagging artifacts. Simulation results comparing output of previous AUM with proposed method show that proposed algorithm makes images properly enhanced, and we know that overshoot and jagging artifacts are many reduced.