• Cartoon and Animation Studies
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• s.29
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• pp.173-207
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• 2012

The four-phased plot which consists of introduction, development, turn and conclusion in the long-story structure tends to be patterned and schematized. The behavior of characters is in line with the beginning of human beings and the plot of comic strips basically has four phases. It is, however, not a simple arrangement but a complex one which was developed by organizing patterns of human power, behavior and emotions. With the results from a survey with college students studying comic strips, this study aims to categorize four characters from the archetypal system by Carol Pearson, four phases of the hero's journey by Joseph Campbell, and the four phases of the plot based on Aristotle's theory, which is the frame of the comic strip structure through supporting evidence extracted from comic strips in an integrated way. In this study, the categorization is performed by simplifying and systemizing a character's life cycle, which is a factor of a story structure in complex comic strips. This study is to identify what comic strip writers express by using the metaphor in the complicated long-story structure of comic strips This study reveals that the structure of introduction, development, turn and conclusion based on the plot theory by Aristotle is the metaphor of human life and fate and that the phases of development in the archetypal system by Carol Pearson, a Jung researcher influenced by Jung's theory are the metaphor of human life and fate. Also, the theories of Joseph Campbell, who also was influenced by Jung, are the metaphor of human life and fate as they projected complex emotions of joy, anger, sorrow, and pleasure onto the archetype of heroes and used the metaphor of the hero's journey. Lastly, the theories are introduced with the approach of 'guide to screenwriters' by Christopher Vogler. Meanwhile, this metaphor is the objective and goal of this study. The comic strips selected for this study seem to have long complex stories which have characters leaving their homes, going through adventures and difficulties, meeting the world in another way, experiencing tension, competition, wars, and hardship and returning home with compensation. They grow mentally and psychologically through their journeys and finally become heroes. They express the meaning of our introspection in a narrative through plots and images of comic strips. This appears complex but the basic structure of long comic strips has four phases of plot. The life style of an extraordinary character traveling for adventures and growing in long comic strips can be divided into four phases symbolizing childhood, adolescence, adulthood, and senescence and it is a psychological growth process. The archetypes of the character can be divided into four phases and the growth process can be explained. The hero's journey symbolized by the character can be also divided into four phases. Through theories, the complex arrangement of four-phased plots in comic strips corresponds with the growth process of introduction, development, turn and conclusion through the stages of life. At the same time, this study found that the characters becoming heroes are the metaphor of introspection and that the characters' growth and life correspond with the four phases in life through long comic strips. Long stories in long comic strips written by comic strip writers show that characters go on their journeys and change their lives through hardship and difficulty by logical construction of plot and their growth processes are presented in archetypal images and they reach introspection as heroes. The readers share time and space through images in comic strips and realize that they had the same experience as the characters emotionally by being moved by the stories.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.225-230
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• 2003

Efficient representation is crucial in the analysis of complex geospatial information. In case of aerial triangulation, most of currently available software are designed as black boxes where only an experienced user would be able to prepares the preformatted input file and interprete the result of the adjustment. This paper introduces a solution to this problem through the UML design of a Graphical User Interface (GUI) for the aerial triangulation task. The design was then implemented with ArcGIS. The error of the exterior orientation of each aerial Imagery was represented with a 3-D error ellipse, enabling the visualization of the adjustment result. The attributes of images and points (control points, tie points and image points) were maintained as a database which enables the searching and querying of adjustment information.

• Fashion & Textile Research Journal
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• v.6 no.1
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• pp.9-16
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• 2004

The purpose of this study is to analyze expression of pluralism in contemporary fashion. This study has three parts. They are to understand the concept of pluralism, to find the fashion environments of pluralism in terms of politics, economics, sociality, culture, science, and art, and to analyze expression of pluralism in contemporary fashion. The concept of pluralism in contemporary fashion is the diversity and compounds of fashion images. The environments of pluralism in contemporary fashion are multinational economic system, virtual world of internet. mass-culture and postmodern art. And expression of pluralism in contemporary fashion is analyzed into publicity. Publicity is expressed by using things of common lifestyle and the past that people used to and are well-known. Horizontality is expressed by coordination of male-female facts and property-poorness without high or low concept. Multi-nation is expressed by mixing various kind of national characteristics and Virtuality is expressed by layering and collaging complex facts that are not connected each other.

• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.83-84
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• 2014

For hydrologic applications, lake levels is very important. As a first step in developing a remote-sensing based approach, lake stage estimation using remote sensing was proposed with the SRTM data from February 2000, which was providing a one-time snapshot. After several steps using contouring, masking, and CED, it was found that iterative contour fitting to a lake outline provided the outstanding result with the operator's decision. If the lake size is large enough, a constant meter of the difference removal due to bias found by Bhang et al. (2007) might be useful for more accurate estimations for the methods. A lake-level snapshot using SRTM data could provide estimates within 0.5 m level of accuracy for large lakes (> $10km^2$) with contouring. Also, even if the processing algorithm is complex, the accuracy was reliable. Overall, we confirmed that this study would provide useful information to ameliorate the quality of the SAR-derived DEMs specifically for water areas and if more expanded, SAR images can fruit result in water monitoring.

• Journal of information and communication convergence engineering
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• v.9 no.6
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• pp.689-694
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• 2011

Cellular automata are discrete dynamical systems, which provide the basis for the synthesis of complex emergent behavior. This paper proposes a new algorithm of digital watermarking based on cellular automata transform (CAT). The idea of two-dimensional CAT is introduced into the algorithm. After the original image is disassembled with 2D CAT, the watermark information is embedded into the Middle-frequency of the carrier picture. Cellular automata have a huge number of combinations, such as gateway values, rule numbers, initial configuration, boundary condition, etc. Using CAT, the robustness of the watermark will be tremendous strengthened as well as its imperceptibility. Experimental results show that this algorithm can resist some usual attacks such as compression, sharpening and so on. The proposed method is robust to different attacks and is more security.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.6
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• pp.198-207
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• 1996

A PSRI (position, scale, and rotation invariant ) feature extraction and automatic target recognition system using a cooperative network and an MLP is proposed. We can extract position invarient features by obtaining the target center using the projection and the moment in preprocessing stage. The scale and rotation invariant features are extracted from the contour projection of the number of edge pixels on each of the concentric circles, which is input to the cooperative network. By extracting the representative PSRI features form the features and their differentiations using max-net and min-net, we can rdduce the number of input neurons of the MLP, and make the resulted automatic target recognition system less sensitive to input variances. Experiments are conduted on various complex images which are shifted, rotated, or scaled, and the results show that the proposed system is very efficient for PSRI feature extractions and automatic target recognitions.

• International Journal of High-Rise Buildings
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• v.9 no.2
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• pp.113-125
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• 2020

Beginning in the late 19th century, construction of skyscrapers spread throughout Chicago, New York City, and then the world as demand of space in buildings and increase of cost of land. With this change curtain wall systems have evolved to be more visually complex; these unique profiles of the skyscraper became powerful images and symbols of our cities. A curtain wall is defined as usually aluminum-framed wall containing in-fills of glass and metal panels. The framing is attached to the building structure and does not carry the floor or roof loads of the building.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.299-307
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• 2016

While segmenting "complex" images (with multiple objects, many details, etc.) we experienced a need to explore new ways for time-efficient and meaningful image segmentation. In this paper we propose a new technique for image segmentation which has only one variable for controlling the expected number of segments. The algorithm focuses on the treatment of pixels in transition zones between various label distributions. Results of the proposed algorithm (e.g. on the Berkeley image segmentation dataset) are comparable to those of GMM or HMM-EM segmentation, but are achieved with significantly reduced computation time.

• Journal of Korea Multimedia Society
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• v.18 no.9
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• pp.1019-1026
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• 2015

In this paper, we propose a new method of eye, face, and lip makeup techniques on the target face image from several makeup examples without losing detail features such as eyelids, eyebrows, hair. After detection of the feature layer for the skin, we applied our makeup techniques to the target face by using a blending technique. We used a cartoon rendering using bilateral filter. In order to smoothly makeup the target face, we created two Gaussian Weight maps for natural skin makeup effects. Our method did not need to perform complex operations, so the makeup results are so natural. Our experimental results show good performances in various makeups.