• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.6
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• pp.23-30
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• 2018

Gordon Cullen, who tried to understand urban landscapes in terms of visual attention, introduced a concept called 'Space and Infinity' in his book 'Townscape'. According to him, urban images like infinity spreading across the sky are more effectively created when we happen to see an open space while walking along a ground-level street than when we look at the sky. This study aims to quantitatively examine if urban observers pay more attention to spaces like pilotis on the bottom of a building. Thus, this study collected observers on actual urban landscape images and partially-edited images and conducted an experiment by adopting Eye-movement Tracking to find out if they actually pay more visual attention to a space like pilotis. This study selected a total of 50 people as research subjects and divided them into two groups. Image 1 was shown to one group, and Image 2 with the pilotis space edited was shown to the other group. As an experiment to find objective evidences on Gordon Cullen's 'Space and Infinity', this study analyzed difference between Image 1 and Image 2, and it was found that the domain of pilotis showed a value five times higher than the average visual attention since it attracted much visual attention although it was very small in area. That is, it has objectively clarified that people get most fascinated with a place with infinite images in the background like a pilotis space out of all the urban landscapes as Gordon Cullen's theory. In addition, the differences in visual concentration of pilotis space by sex, by subject was examined, and there was no significant difference in visual concentration of pilotis space by gender. As a result of examining the difference of visual concentration by classifying the subjects into architectural related major, the major group showed higher frequency of viewing than the non - major group.

• Journal of Astronomy and Space Sciences
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• v.23 no.1
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• pp.29-38
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• 2006

This paper presents an Image Motion Compensation (IMC) algorithm for the Korea's Communication, Ocean, and Meteorological Satellite (COMS)-1. An IMC algorithm is a priority component of image registration in Image Navigation and Registration (INR) system to locate and register radiometric image data. Due to various perturbations, a satellite has orbit and attitude errors with respect to a reference motion. These errors cause depointing of the imager aiming direction, and in consequence cause image distortions. To correct the depointing of the imager aiming direction, a compensation algorithm is designed by adapting different equations from those used for the GOES satellites. The capability of the algorithm is compared with that of existing algorithm applied to the GOES's INR system. The algorithm developed in this paper improves pointing accuracy by 40%, and efficiently compensates the depointings of the imager aiming direction.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.41-50
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• 2004

Since the MPEG-4 visual standard enables content-based functionalities, it is necessary to extract video objects from video sequences. Segmentation algorithms can largely be classified into two different categories: automatic segmentation and user-assisted segmentation. In this paper, we propose a new user-assisted image segmentation method based on the active contour. If we define a shape space as a set of all possible variations from the initial curve and we assume that the shape space is linear, it can be decomposed into the column space and the left null space of the shape matrix. In the proposed method, the shape space vector in the column space describes changes from the initial curve to the imaginary feature curve, and a dynamic graph search algorithm describes the detailed shape of the object in the left null space. Since we employ the shape matrix and the SUSAN operator to outline object boundaries, the proposed algorithm can ignore unwanted feature points generated by low-level image processing operations and is, therefore, applicable to images of complex background. We can also compensate for limitations of the shape matrix with a dynamic graph search algorithm.

• Journal of Advanced Navigation Technology
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• v.13 no.6
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• pp.984-990
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• 2009

Halftoning is very important image processing techniques in the digital printing industry which is a process of converting a continuous-tone image to bi-level tone image. In this paper we introduce a new digital halftoning method based on maze generation algorithm as a replacement algorithm of halftoning with space-filling curve. Previous error-diffusion methods based on space-filling curve suffer from regular pattern artifacts from uniform scan pattern. We use maze generation algorithm to remove this undesirable pattern of space-filling curve method.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.22-30
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• 2024

Image compression-decompression methods have become increasingly crucial in modern times, facilitating the transfer of high-quality images while minimizing file size and internet traffic. Historically, early image compression relied on rudimentary codecs, aiming to compress and decompress data with minimal loss of image quality. Recently, a novel compression framework leveraging colorization techniques has emerged. These methods, originally developed for infusing grayscale images with color, have found application in image compression, leading to colorization-based coding. Within this framework, the encoder plays a crucial role in automatically extracting representative pixels-referred to as color seeds-and transmitting them to the decoder. The decoder, utilizing colorization methods, reconstructs color information for the remaining pixels based on the transmitted data. In this paper, we propose a novel approach to image compression, wherein we decompose the compression task into grayscale image compression and colorization tasks. Unlike conventional colorization-based coding, our method focuses on the colorization process rather than the extraction of color seeds. Moreover, we employ the Denoising Diffusion Null-Space Model (DDNM) for colorization, ensuring high-quality color restoration and contributing to superior compression rates. Experimental results demonstrate that our method achieves higher-quality decompressed images compared to standard JPEG and JPEG2000 compression schemes, particularly in high compression rate scenarios.

• Korean Institute of Interior Design Journal
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• v.26 no.2
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• pp.3-12
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• 2017

This study has analyzed the features of attention to spacial composition seen in "Seeing ${\leftrightarrow}$ Seen" Correlation of continuous move in the space. The eye-tracking was employed for collecting the data of attention features to the space so that the correlation between visual perception and space could be estimated through the attention features to the difference between spacial composition and display. First, it was confirmed that the attention features varied according to the structure of shops and the exposure degree of selling space, which revealed that, while causing the customers' less attention to both sides of shops, the vanishing-point structure characteristically made their eyes focused on the central part. Second, their initial observation activities were found to be active at the height of their eyes. Third, 10 images were selected as objects for continuous experiment. There was a concern that the central part of each image would be paid intense attention to during the initial observation, but only two of those were found to be so. Fourth, there had been a study result of eye-tracking experiment that the attention had been concentrated on the central part of the image first seen. This study, however, revealed that such phenomenon is limited to the first image. Accordingly, it is necessary to draw up such method for ensuring reliability in order to use the data acquired from any eye-tracking experiment as exclusion of the initial attention time to the first image or of unemployment of the initial image-experiment to analysis.

• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1418-1432
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• 1997

Most general content_based image retrieval techniques use color and texture as retrieval indices. In color techniques, color histogram and color pair based color retrieval techniques suffer from a lack of spatial information and text. And This paper describes the design and implementation of content_based image retrieval system using color space and keywords. The preprocessor for image retrieval has used the coordinate system of the existing HSI(Hue, Saturation, Intensity) and preformed to split One image into chromatic region and achromatic region respectively, It is necessary to normalize the size of image for 200*N or N*200 and to convert true colors into 256 color. Two color histograms for background and object are used in order to decide on color selection in the color space. Spatial information is obtained using a maximum entropy discretization. It is possible to choose the class, color, shape, location and size of image by using keyword. An input color is limited by 15 kinds keyword of chromatic and achromatic colors of the Korea Industrial Standards. Image retrieval method is used as the key of retrieval properties in the similarity. The weight values of color space ${\alpha}(%)and\;keyword\;{\beta}(%)$ can be chosen by the user in inputting the query words, controlling the values according to the properties of image_contents. The result of retrieval in the test using extracted feature such as color space and keyword to the query image are lower that those of weight value. In the case of weight value, the average of te measuring parameters shows approximate Precision(0.858), Recall(0.936), RT(1), MT(0). The above results have proved higher retrieval effects than the content_based image retrieval by using color space of keywords.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.4
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• pp.232-237
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• 2013

This paper presents image database retrieval based on maximum color occurrenceusing Hue, Saturation and Value (HSV) color space. Our system is based on color segmentation. We dividedthe image into n number of areas based on different selected ranges of hue and value, then each area is partitioned into m number of segments based on the number of pixels it contains, after this we calculated the maximumcolor occurrence in each segment and used its HSV value. This is used as a feature vector.

• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.186-197
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• 2012

The purpose of the thesis is to answer the question on how the visual image content, being the original content, should be adapted to and represented as a spatial content. The thesis focuses on adaptation as the key in the conversion process of visual image content to a themed space. There are many published studies dealing with storytelling, adaptation from books to movies and TV shows, or from movies to games and vice versa. On the contrary, when it comes to adaptation from visual image content to spatial content, noticeably few studies were done on the method, and fewer studies view adaptation as the prior step of storytelling. This study first defines adaptation, and then applies the methods of Gianetty and Dudley which is further incorporated into the conversion of visual image content into a themed space. It then turns the attention to the characteristics of themed spaces. A case study highlights that a themed space is a spatial representation of the story, image and action in the visual image content, and analyze the type of adaptation made. The study results draws two conclusions; adaptation must be carried out prior to the storytelling of the spatial content; and opposed to a third-person view of the visual image content, the main factor in a themed space is first-hand experience. Thus, the thesis suggests that conversion from visual image content to themed spaces are not merely imitative but is a full range of recreation of a new content. It is expected that more detailed analyses on the particulars will lead to feasible outcome on implementing various methods of adaptation and bring about effective conversions between the visual image contents and themed spaces.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.940-942
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• 2003

In an attempt to enhance the visual effect of SPOT image, this study develops a neural network algorithm to transform SPOT false color into simulated true color. The method has been tested using Landsat TM and SPOT images. The qualitative and quantitative comparisons indicate that the striking similarity can be found between the true and simulated true images in terms of the visual looks and the statistical analysis.