• The KIPS Transactions:PartB
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• v.9B no.6
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• pp.715-726
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• 2002

In this paper, we construct real-time moving picture encoder based on fractal theory by using general purpose digital signal processors. The constructed encoder is implemented using two fixed-point general DSPs (ADSP2181) and performs image encoding by three stage pipeline structure. In the first pipeline stage, the image grabber acquires image data from NTSC standard image signals and stores digital image into frame memory. In the second stage, the main controller encode image dada using fractal algorithm. The last stage, output controller perform Huffman coding and result the coded data via RS422 port. The performance tests of the constructed encoder shows over 10 frames/sec encoding speed for QCIF data when all the frames are encoded. When we encode the images using the interframe and redundency based on the proposed algorithms, encoding speed increased over 30 frames/sec in average.

• Journal of Digital Convergence
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• v.10 no.4
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• pp.191-197
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• 2012

In this paper we present creating 3D image from 2D image by extract initial depth values calculated from focal values. The initial depth values are created by using the extracted focal information, which is calculated by the comparison of original image and Gaussian filtered image. This initial depth information is allocated to the object segments obtained from normalized cut technique. Then the depth of the objects are corrected to the average of depth values in the objects so that the single object can have the same depth. The generated depth is used to convert to 3D image using DIBR(Depth Image Based Rendering) and the generated 3D image is compared to the images generated by other techniques.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3C
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• pp.296-306
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• 2003

In this paper, algorithm for non-iterative decoding method is proposed and fractal image decoder based on non-iterative fractal decoding algorithm used general purpose digital signal processors is designed and implemented. The algorithm is showed that the attractor image can be obtained analytically whe n the image is encoded using the fractal algorithm proposed by Monro and Dudbridge, in which the corresponding domain block for a range block is fifed. Using the analytical formulas, we can obtain the attractor image without iteration procedure. And we get general formulas of obtained analytical formulas. Computer simulation results for various test images show that we can increase the image decoding speed by more than five times when we use the analytical formulas compared to the previous iteration methods. The fractal image decoder contains two ADSP2181's and perform image decoding by three stage pipeline structure. The performance tests of the implemented decoder is elapsed 31.2ms/frame decoding speed for QCIF data when all the frames are decoded. The results enable us to process the real-time fractal decoding over 30 frames/sec.

• Journal of The Korean Society of Integrative Medicine
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• v.10 no.4
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• pp.251-259
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• 2022

Purpose : This study was conducted to check the effect on nursing college students' major satisfaction, adjustment to college life and nurse's image nursing students before clinical practical education. Methods : The study surveyed 209 college students majoring in nursing science in the city of B for the period of April through May 2022. The collected data were analyzed using SPSS/WIN 22.0 to determine the frequency, percentage ratio, average, and standard deviation. Statistical analyses included the t-test, analysis of variance, pearson's correlation coefficients. Results : As a result of this study, the average degree of satisfaction with majors was 3.88±.50, the average of college life adaptation was 3.26±.47, and the average of the nurse image was 3.90±.51. The major satisfaction according to the general characteristics of the study subjects showed a statistically significant difference in the motive for choosing a department (F=3.70, p=.003) and the thought of a nursing job (F=2.95, p=.004). The adjustment to college life according to the general characteristics of the study subjects showed a statistically significant difference in grade (F=3.50, p=.001), department selection motivation (F=2.69, p=.022) showed a statistically significant difference. The nurse image showed a statistically significant difference in residence type (F=6.00, p=.001) and nursing job thinking (F=2.11, p=.036). The correlation between the variables of the study subjects showed that major satisfaction was found to have a positive correlation with adjustment college life (r=.51, p<.001) and nurse image (r=.54, p<.001). It was found that adjustment college life had a positive correlation with the nurse image (r=.32, p<.001). Conclusion : The higher the degree of satisfaction with the major of nursing students prior to clinical practice education, the higher the degree of adaptation to college life. It is need to intervention studies that can improve the image of positive nursing.

• Journal of radiological science and technology
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• v.47 no.3
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• pp.175-182
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• 2024

Advanced modeled iterative reconstruction (ADMIRE) represents a repetitive reconstruction method that can adjust strength and kernel, each of which are known to affect computed tomography (CT) image quality. The aim of this study was to quantitatively analyze the noise and spatial resolution of CT images according to ADMIRE control factors. Patient images were obtained by applying ADMIRE strength 2 and 3, and kernel B40 and B59. For quantitative evaluations, the noise level, spatial resolution, and overall image quality were measured using coefficient of variation (COV), edge rise distance (ERD), and natural image quality evaluation (NIQE). The superior values for the average COV, ERD, and NIQE results were obtained for the ADMIRE reconstruction conditions of ADMIRE 2 + B40, ADMIRE 3 + B59, and ADMIRE3 + B59. NIQE, which represents the overall image quality based on no-reference, was about 6.04 when using ADMIRE 3 + B59, showing the best result among the reconstructed image acquisition conditions. The results of this study indicate that the ADMIRE strength and kernel chosen for use in ADMIRE reconstruction have a significant impact on CT image quality. This highlights the importance of adjusting to the control factors in consideration of the clinical environment.

• Korean Institute of Interior Design Journal
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• no.26
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• pp.11-18
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• 2001

This study explores the interior image preferred by females living in urban areas. It also examines the relationship between interior image and socio-demographic characteristics such as age, marital status, employment status, total household income. The target population of this study was 301 adult females living in Kwangju City. The data were analyzed with frequency, percentage, General Linear Model, and Duncan's multiple range test using the SAS package. The major findings of this study were as follows. 1) The majority of the females generally preferred modernity of interior image to traditionalism. Also they preferred feminity of interior image to masculinity and complexity to simplicity. 2) Females in the age of 40s were more likely to prefer simple and oriental-traditionalism image to those under the age of 30s. 3) Those with the higher total household income were more 1ike1y prefer western-traditionalism image to those with the lower. But those with the lower household income were more tended to prefer modernity image to those with the higher.

• Transactions on Electrical and Electronic Materials
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• v.18 no.5
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• pp.273-278
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• 2017

Recently, one of the areas where research is being actively conducted is the Internet of Things (IoT). The field of using the Internet of Things system is increasing, coupled with a remarkable increase of the use of the camera. However, general cameras used in the Internet of Things have limited viewing angles as compared to those available to the human eye. Also, cameras restrict observation of objects and the performance of observation. Therefore, in this paper, we propose a panoramic image stitching method using feature extraction and matching based on an embedded system. After extracting the feature of the image, the speed of image stitching is improved by reducing the amount of computation using the necessary information so that it can be used in the embedded system. Experimental results show that it is possible to improve the speed of feature matching and panoramic image stitching while generating a smooth image.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.251-256
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• 2004

The image classification is one of the most important studies in the remote sensing. In general, the MLC(Maximum Likelihood Classification) classification that in consideration of distribution of training information is the most effective way but it produces a bad result when we apply it to actual hyperspectral image with the same classification technique. The purpose of this research is to reveal that which one is the most effective and suitable way of the classification algorithms iii the hyperspectral image classification. To confirm this matter, we apply the MLC classification algorithm which has distribution information and SAM(Spectral Angle Mapper), SFF(Spectral Feature Fitting) algorithm which use average information of the training class to both multispectral image and hyperspectral image. I conclude this result through quantitative and visual analysis using confusion matrix could confirm that SAM and SFF algorithm using of spectral pattern in vector domain is more effective way in the hyperspectral image classification than MLC which considered distribution.

• Journal of the Korea Society for Simulation
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• v.10 no.3
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• pp.59-70
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• 2001

Typical low-level image processing tasks require thousands of operations per pixel for each input image. Traditional general-purpose computers are not capable of performing such tasks in real time. Yet important features of traditional computers are not exploited by low-level image processing tasks. Since storage requirements are limited to a small number of low-precision integer values per pixel, large hierarchical memory systems are not necessary. The mismatch between the demands of low-level image processing tasks and the characteristics of conventional computers motivates investigation of alternative architectures. The structure of the tasks suggests employing an array of processing elements, one per pixel, sharing instructions issued by a single controller. In this paper we implemented various image processing filtering using the format converter. Also, we realized from conventional gray image process to color image process. This design method is based on realized the large processor-per-pixel array by integrated circuit technology This format converter design has control path implementation efficiently, and can be utilize the high technology without complicated controller hardware.

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1138-1156
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• 2021

Emotional semantics are the highest level of semantics that can be extracted from an image. Constructing a system that can automatically recognize the emotional semantics from images will be significant for marketing, smart healthcare, and deep human-computer interaction. To understand the direction of image emotion recognition as well as the general research methods, we summarize the current development trends and shed light on potential future research. The primary contributions of this paper are as follows. We investigate the color, texture, shape and contour features used for emotional semantics extraction. We establish two models that map images into emotional space and introduce in detail the various processes in the image emotional semantic recognition framework. We also discuss important datasets and useful applications in the field such as garment image and image retrieval. We conclude with a brief discussion about future research trends.