• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.79-89
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• 2022

Images taken using drones have been applied to fields that require rapid decision-making as they can quickly construct high-quality 3D spatial information for small regions. To construct spatial information based on drone images, it is necessary to determine the relationship between images by extracting keypoints between adjacent drone images and performing image matching. Therefore, in this study, three study regions photographed using a drone were selected: a region where parking lots and a lake coexisted, a downtown region with buildings, and a field region of natural terrain, and the performance of AKAZE (Accelerated-KAZE), BRISK (Binary Robust Invariant Scalable Keypoints), KAZE, ORB (Oriented FAST and Rotated BRIEF), SIFT (Scale Invariant Feature Transform), and SURF (Speeded Up Robust Features) algorithms were analyzed. The performance of the keypoints extraction algorithms was compared with the distribution of extracted keypoints, distribution of matched points, processing time, and matching accuracy. In the region where the parking lot and lake coexist, the processing speed of the BRISK algorithm was fast, and the SURF algorithm showed excellent performance in the distribution of keypoints and matched points and matching accuracy. In the downtown region with buildings, the processing speed of the AKAZE algorithm was fast and the SURF algorithm showed excellent performance in the distribution of keypoints and matched points and matching accuracy. In the field region of natural terrain, the keypoints and matched points of the SURF algorithm were evenly distributed throughout the image taken by drone, but the AKAZE algorithm showed the highest matching accuracy and processing speed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.556-559
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• 2008

In this study, an automated ultrasonic testing system and post signal and image processing techniques are developed in order to construct ultrasonic flaw images in weldments. The automated ultrasonic testing system developed in the present study adopted an 8 channel pulser/receiver-ADC unit and a 2 axis motion driving unit and the post signal and image processing algorithms are built into the system program of the automated ultrasonic testing system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2851-2865
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• 2014

To improve the rate-distortion performance of distributed video compressive sensing (DVCS), the adaptive sparse basis and nonlocal similarity of video are proposed to jointly reconstruct the video signal in this paper. Due to the lack of motion information between frames and the appearance of some noises in the reference frames, the sparse dictionary, which is constructed using the examples directly extracted from the reference frames, has already not better obtained the sparse representation of the interpolated block. This paper proposes a method to construct the sparse dictionary. Firstly, the example-based data matrix is constructed by using the motion information between frames, and then the principle components analysis (PCA) is used to compute some significant principle components of data matrix. Finally, the sparse dictionary is constructed by these significant principle components. The merit of the proposed sparse dictionary is that it can not only adaptively change in terms of the spatial-temporal characteristics, but also has ability to suppress noises. Besides, considering that the sparse priors cannot preserve the edges and textures of video frames well, the nonlocal similarity regularization term has also been introduced into reconstruction model. Experimental results show that the proposed algorithm can improve the objective and subjective quality of video frame, and achieve the better rate-distortion performance of DVCS system at the cost of a certain computational complexity.

• Journal of Korean Academy of Nursing
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• v.45 no.3
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• pp.429-438
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• 2015

Purpose: This study was conducted to develop key performance indicators (KPIs) for home care nursing (HCN) based on a balanced scorecard, and to construct a performance prediction model of strategic objectives using the Bayesian Belief Network (BBN). Methods: This methodological study included four steps: establishment of KPIs, performance prediction modeling, development of a performance prediction model using BBN, and simulation of a suggested nursing management strategy. An HCN expert group and a staff group participated. The content validity index was analyzed using STATA 13.0, and BBN was analyzed using HUGIN 8.0. Results: We generated a list of KPIs composed of 4 perspectives, 10 strategic objectives, and 31 KPIs. In the validity test of the performance prediction model, the factor with the greatest variance for increasing profit was maximum cost reduction of HCN services. The factor with the smallest variance for increasing profit was a minimum image improvement for HCN. During sensitivity analysis, the probability of the expert group did not affect the sensitivity. Furthermore, simulation of a 10% image improvement predicted the most effective way to increase profit. Conclusion: KPIs of HCN can estimate financial and non-financial performance. The performance prediction model for HCN will be useful to improve performance.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.965-976
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• 2020

We present in this work a segmentation method of E. coli bacterial images generated via phase contrast microscopy using a deep learning based hybrid feature generation. Unlike conventional machine learning methods that use the hand-crafted features, we adopt the denoising autoencoder in order to generate a precise and accurate representation of the pixels. We first construct a hybrid vector that combines original image, difference of Gaussians and image gradients. The created hybrid features are then given to a deep autoencoder that learns the pixels' internal dependencies and the cells' shape and boundary information. The latent representations learned by the autoencoder are used as the inputs of a softmax classification layer and the direct outputs from the classifier represent the coarse segmentation mask. Finally, the classifier's outputs are used as prior information for a graph partitioning based fine segmentation. We demonstrate that the proposed hybrid vector representation manages to preserve the global shape and boundary information of the cells, allowing to retrieve the majority of the cellular patterns without the need of any post-processing.

• Journal of the Korea Society of Computer and Information
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• v.4 no.1
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• pp.47-53
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• 1999

In medical field, the computer has been used in the automatic processing of data derived in hospital. the automation of diagonal devices, and processing of medical digital images. In this paper, we classify red blood cell into 16 class including normal cell to the automation of blood analysis to diagnose disease. First, using UNL Fourier and invariant moment algorithm, we extract features of red blood cell from blood cell image and then construct multi-layer backpropagation neural network to recognize. We proof that the system can give support to blood analyzer through blood sample analysis of 10 patients.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.3
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• pp.248-254
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• 2009

The worn crater wear geometry of coated tools after machining has been configured by using Confocal Laser Scanning Microscopy(CLSM) and the Wavelet-based filtering technique. The CLSM can be well suited to construct the three-dimensional crater wear on the rake surfaces of coated tips. However, The raw heightness data of HEI(height encoded image) acquired by CLSM must be filtered due to the electronic and imaging noise occurring in constructing the crater image. So the Wavelet-based filtering algorithm is necessary to denoise the shape features in a micro scales so as to realize accurate crater wear topography analysis. The crater wear patterns filtered enable us to predict the crater wear shape in order to study the tool wear evolution. The study shows that the technique by combining the CLSM and Wavelet-based filtering is an excellent one to obtain the geometries of worn tool rake surfaces over a wide range of surface resolution in a micro scale.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.9_10 s.157
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• pp.1476-1484
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• 2006

This study is on the esthetic characteristics of Tuxedo-Look in the modern women fashion from 1990s to the present. It could contribute to understand the aspects and the sense of beauty of the modern fashion. This study is performed by reviewing the precedent studies, related literature and deploying fashion portfolios, domestic and international fashion magazines for the exploratory study. The results of the study are the following. First, Tuxedo-Look expresses the androgenous image which weakens the superficial message of masculinity or femininity and produces the unified image of men and women. Tuxedo-Look, a symbolic male dress item, is brought in the women clothes and it is recreated by design modification, new wearing style, and producing effects. Second, Tuxedo-Look emphasizes femininity by using a exposure and body line stressed design and matching the women dress items with various materials and colors or tuxedo. Third, Tuxedo-Look suggests a dismantling point of view such as exaggeration, distortion, secession, and breaking from the convention. Tuxedo-Look expresses uncertain value by breaking up the symbolic valueby coordinating with casual items and denies formal construct of tuxedo such as perfect balance, symmetrical silhouette, formality, totality.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.2
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• pp.322-327
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• 2003

Based on dynamic muscle model to construct efficient face animation in this paper 30 face modelling techniques propose. Composed face muscle by faceline that connect 256 point and this point based on dynamic muscle model, and constructed wireframe because using this. After compose standard model who use wireframe, because using front side and side 2D picture, enforce texture mapping and created 3D individual face model. Used front side of characteristic points and side part for correct mapping, after make face that have texture coordinates using 2D coordinate of front side image and front side characteristic points, constructed face that have texture coordinates using 2D coordinate of side image and side characteristic points.

• Korean Institute of Interior Design Journal
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• v.13 no.4
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• pp.12-20
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• 2004

The purposes of this study were to identify styles of contemporary interior design, construct their images, and find out the relation of the identified styles to the structure images. Content analysis was used as the main method of this study, and the focus of the analysis was on a typological approach. Two hundred interior design photos were drawn from five different interior design magazines published in the past ten years, and ,they were analyzed by interior design professionals. Contemporary interior design was classified into ten styles: romantic, ethnic, classical, high tech, elegant, country, modern, minimal, natural, and causal. Given the ten styles, five images of interior design were identified - simple, comfortable, rustic, classical, and delightful. With regard to the relationships between 10 styles and 5 images of interior design, the this study found that the romantic style was related to the images of rustic and classical, the ethnic style to the images of comfortable, classical, and delightful, the classical style to the image of classical, the high tech style to the images of classical and rustic, the elegant style to the images of simple and classical, the country style to the images of comfortable and rustic, the modern style to the images of simple and delightful, the minimal style to the image of comfortable, the natural style to the images of comfortable and delightful, and the causal style to the images of comfortable and delightful.