• Journal of architectural history
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• v.23 no.1
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• pp.51-62
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• 2014

Architecture is a product of numerous influences, as shown in the apprenticeships of Kim, Jung-Up and Kim, Swoo-Geun with Le Corbusier's influences. Therefore, its identity is need to be re-defined based on such complex relationships. The rhetorical images of 'the Map of Misreading', as the core of the poetic identification proposed by Harold Bloom's 'the Theory of Influence', provide an efficient way of explaining the relations between architectural apprenticeships and identities. This research is to re-build a new methodology of architectural criticism based on it. The diachronic transformations of the architecture of Seung, Hyo-Sang also had very characteristic 'revisionary ratios' about his precursor Kim, Swoo-Geun. As an antithetic stance of his precursor's final phase, his early days works pursued continuously geometric abstraction and objective images of the architecture of Adolf Loos. However, his recent works are showing the obvious symptoms of regression to his origins. Finally, the architectural identity should be re-conceptualized as a complexity, based on inter-textuality from complex influences. This new architectural identity can be reflected into the modern obsessive identity.

• Journal of Information Processing Systems
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• v.10 no.2
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• pp.283-299
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• 2014

Skin detection is used in many applications, such as face recognition, hand tracking, and human-computer interaction. There are many skin color detection algorithms that are used to extract human skin color regions that are based on the thresholding technique since it is simple and fast for computation. The efficiency of each color space depends on its robustness to the change in lighting and the ability to distinguish skin color pixels in images that have a complex background. For more accurate skin detection, we are proposing a new threshold based on RGB and YUV color spaces. The proposed approach starts by converting the RGB color space to the YUV color model. Then it separates the Y channel, which represents the intensity of the color model from the U and V channels to eliminate the effects of luminance. After that the threshold values are selected based on the testing of the boundary of skin colors with the help of the color histogram. Finally, the threshold was applied to the input image to extract skin parts. The detected skin regions were quantitatively compared to the actual skin parts in the input images to measure the accuracy and to compare the results of our threshold to the results of other's thresholds to prove the efficiency of our approach. The results of the experiment show that the proposed threshold is more robust in terms of dealing with the complex background and light conditions than others.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.30 no.2
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• pp.1-10
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• 2016

A system which provides multispectral near-IR and visible gray images of objects is constructed and an algorithm is derived to acquire a natural color image of objects from the gray images. A color image of 24 color patches is obtained by recovering their CIE (International Commission on Illumination) LAB color coordinates $L^*$, $a^*$, $b^*$ from their gray images using the algorithm based on polynomial regression. The system is composed of a custom-designed LED illuminator emitting multispectral near-IR illuminations, fluorescent lamps and a monochrome digital camera. Color reproducibility of the algorithm is estimated in CIELAB color difference ${\Delta}E^*_{ab}$. And as a result, if yellow and magenta color patches with around 10 ${\Delta}E^*_{ab}$ are disregarded, the average ${\Delta}E^*_{ab}$ is 2.9, and this value is within the acceptability tolerance for quality evaluation for digital color complex image.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.55-62
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• 2010

Human visual attention system has a remarkable ability to interpret complex scenes with the ease and simplicity by selecting or focusing on a small region of visual field without scanning the whole images. In this paper, a novel feature map generation and integration method for attention based visual information processing system is proposed. The depth information obtained from a stereo pair of images is exploited as one of spatial visual features to form a set of topographic feature maps in our approach. Comparative experiments show that correct detection rate of visual attention regions improves by utilizing depth feature compared to the case of not using depth feature.

• Korean Institute of Interior Design Journal
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• no.12
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• pp.78-86
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• 1997

The purpose of this study was to determine the relationships between personality and interior environmental disposition, such as disposition toward traditional/modern, feminine/ masculine and simple/complex characteristics. Korean Testing Center's standardized test which measures activity, emotional stability, dominance, reflectiveness, sociability, autonomy, and achievement was used to measure personality. The three key disposition variables were measured using a visual instrument which was developed in this study. To create images, 3$\times$2$\times$2 factorial composition producing 12 types of images was used. Four set of images were developed to measure each categories of each dispositional characteristic controlling other systematic variables and extraneous variables effects. Thereby total 48 visual images were simulated. The subjects were 107 students. Data were analyzed using frequency, percentage, chi-square. test and pearson's correlation coefficients. Major findings were as follows; 1)Disposition toward oriental tradition were more likely appeared in higher emotional stability personality 2) Disposition toward tradition were more likely to be dominated than one toward modern in case of higher autonomy personality.

• Journal of Korea Multimedia Society
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• v.21 no.10
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• pp.1150-1161
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• 2018

Classification is widely used in medical images to categorize patients and non-patients. However, conventional classification requires a complex procedure, including some rigid steps such as pre-processing, segmentation, feature extraction, detection, and classification. In this paper, we propose a novel convolutional neural network (CNN), called LeukemiaNet, to specifically classify two different types of leukemia, including acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML), and non-cancerous patients. To extend the limited dataset, a PCA color augmentation process is utilized before images are input into the LeukemiaNet. This augmentation method enhances the accuracy of our proposed CNN architecture from 96.9% to 97.2% for distinguishing ALL, AML, and normal cell images.

• Advances in Automotive Engineering
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• v.1 no.1
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• pp.143-152
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• 2018

In this study an economical image stitching algorithm for use in automotive industry is developed for retrofittable panoramic image assistance applications. The aim of this project is to develop a driving assistance system known as Panoramic Parking Assistance (PPA) which is cheap, retrofittable and compatible for every type of automobiles. PPA generates bird's eye view image using cameras installed on the automobiles. Image stitching requires to get bird's eye view position of the vehicle. Panoramic images are wide area images that cannot be available by taking one shot, attained by stitching the overlapping areas. To achieve correct stitching many algorithms are used. This study includes some type of these algorithms and presents a simple one that is economical and practical. Firstly, the mathematical model of a wide view of angle camera is provided. Then distorted image correction is performed. Stitching is implemented by using the SIFT and SURF algorithms. It has been seen that using such algorithms requires complex image processing knowledge and implementation of high quality digital processors, which would be impracticle and costly for automobile use. Thus a simpler algorithm has been developed to decrase the complexity. The proposed algorithm uses one matching point for every couple of images and has ease of use and does not need high power processors. To show the efficiency, images coming from four distinct cameras are stitched by using the algorithm developed for the study and usability for automotive application is analyzed.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.14 no.1
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• pp.71-80
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• 1984

The author has studied each landmark for successful interpretation in the radiograph of the head that have the complex anatomic structures, using panoramic radiograph, postero-anterior cephalometric radiograph, lateral cephalometric radiograph, Waters' radiograph of the skull. The anatomic structures of the human dry skull attached by radiopaque materials were taken radiographs and analysed comparatively. The results were as follows: 1. The overall anatomic structures of the mandible showed sharp images in the panoramic radiograph than other radiographs with relatively less distortion, superimposition, blurring of the image. 2. The anatomic structures were situated on sagital plane of the skull showed blurred images in panoramic radiograph than other radiographs. 3. The anatomic structures which were situated on the basal portion of the skull showed blurred and secondary images in the panoramic radiograph than other radiographs. 4. In the panoramic radiograph, the lower 3rd portion of the orbit appeared to be superimposed with the superior portion of the maxillary sinus and the medial and lateral surface of the nasal cavity showed extensively superimposition of the orbit and the maxillary sinus, which images showed blurring. 5. The inferior surface and posterior surface of maxillary sinus showed to be good image in the panoramic radiograph than other radiographs. 6. In the panoramic radiograph, line of maxillary bone between lateral pterygoid plate, line of maxillary bone between zygomatic bone showed distinct image with another structures.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2203-2208
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• 2014

The Hough transform (HT), that is a typical algorithm for detecting lines in images, needs considerable computational costs and easily detects pseudo-lines on the real world images, because of the large amount of features generated by their complex background or noise. This paper proposes an improved HT that add a preprocessing to estimate the validity of features to the conventional HT. The feature estimation can remove a lot of inessential features for the line detection using a pattern of $3{\times}3$ block features. Experiments using various images show that the proposed algorithm saves computational costs by removing 14%~58% of features depending on images and besides it is superior to the conventional HT in valid line detection.

• Smart Structures and Systems
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• v.30 no.1
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• pp.17-34
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• 2022

For steel structures, fatigue cracks are critical damage induced by long-term cycle loading and distortion effects. Vision-based crack detection can be a solution to ensure structural integrity and performance by continuous monitoring and non-destructive assessment. A critical issue is to distinguish cracks from other features in captured images which possibly consist of complex backgrounds such as handwritings and marks, which were made to record crack patterns and lengths during periodic visual inspections. This study presents a parametric study on image-based crack identification for orthotropic steel bridge decks using captured images with complicated backgrounds. Firstly, a framework for vision-based crack segmentation using the atrous convolution-based Deeplapv3+ network (ACDN) is designed. Secondly, features on crack images are labeled to build three databanks by consideration of objects in the backgrounds. Thirdly, evaluation metrics computed from the trained ACDN models are utilized to evaluate the effects of obstacles on crack detection results. Finally, various training parameters, including image sizes, hyper-parameters, and the number of training images, are optimized for the ACDN model of crack detection. The result demonstrated that fatigue cracks could be identified by the trained ACDN models, and the accuracy of the crack-detection result was improved by optimizing the training parameters. It enables the applicability of the vision-based technique for early detecting tiny fatigue cracks in steel structures.