• The Research Journal of the Costume Culture
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• v.19 no.5
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• pp.1061-1074
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• 2011

This study was conducted based on a comparative analysis of design-specific features prevalent in the Women's Wear Collection S/S 2011. As the method of this study, the denim styles were classified by various fashion design factors consisting of silhouette, fit, color, and textile fabric, which were extracted from an image database. The properties of denim fabrics associated with each fashion image were investigated to inform fabric development and washing. The results of the study show that the dense and glossy surface of the denim fabric represent a modern trend, which can be achieved by blending lyocell, tencel and rayon or by using different textiles, such as lightweight plain weave and satin instead of twill. For casual look, various washing effects were utilized jean's casual feeling like freedom and activities, while in a modern image, washing effects was restricted. And a glossy textile offers a simple modern look. The Modern image represents a simple H-silhouette and wide or straight fit in bottoms as well. Brightness can be adjusted by washing-induced bleaching. High brightness gives an elegant image, while low brightness makes a casual image. The purpose of this study is to configure a database for the development of design in the growing women's casual wear market. In addition, This study, in which the elements for specific fashion image-making were analyzed, can be used as a reference for developing denim style and fabric.

• Journal of the Semiconductor & Display Technology
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• v.9 no.3
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• pp.17-21
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• 2010

As the compact and easily accessible handheld devices, such as cellular phones and MP3 players equipped with image acquisition functionality, are becoming widely available among common users, various applications of images are rapidly increasing. Image related services and software such as web-based image presentation and image manipulation for personal or commercial purpose enable users to view contents of remote image archive and to manipulate enormous amount of images in local or network based storage as well. It is necessary for users to identify the images efficiently so that the same images are perceived as one physical entity instead of recognizing them as different images as the trends are getting stronger. In order to support this environment, we propose a method that generates image identifiers or indexing for images within a solid and efficient manner. The proposed image identifier utilizes multiple index values. The integration of component index values creates a unique composite value that can be used as a file name, file system identifier, or database index. Our experimental results on generation of constituent index values have shown favorable results.

• Journal of the Korea Society for Simulation
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• v.29 no.4
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• pp.21-31
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• 2020

NCTR(Non-Cooperative Target Recognition) refers to the function of radar to identify target on its own without support from other systems such as ELINT(ELectronic INTelligence). ISAR(Inverse Synthetic Aperture Radar) image is one of the representative methods of NCTR, but it is difficult to automatically classify the target without an identification database due to the significant changes in the image depending on the target's maneuver and location. In this study, we discuss how to build an identification database using simulation and deep-learning technique even when actual images are insufficient. To simulate ISAR images changing with various radar operating environment, A model that generates and learns images through the process named 'Perfect scattering image,' 'Lost scattering image' and 'JEM noise added image' is proposed. And the learning outcomes of this model show that not only simulation images of similar shapes but also actual ISAR images that were first entered can be classified.

• Journal of Broadcast Engineering
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• v.7 no.2
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• pp.136-144
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• 2002

In this paper, a novel approach that makes use of both shape and color information to retrieve character images in terms of similarity distance from a large-capacity image database or from a streaming image database, in particular, character image logo or trademark. In order to combine both features of completely different characteristics bipartite matching has been employed in computing similarity distance, The proposed method turned out to bealso very effective in matching natural object or human-drawn images whose shape varies substantially.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.1
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• pp.68-78
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• 2005

A new emotion-based image retrieval method is proposed in this paper. The research was motivated by Soen's evaluation of human emotion on color patterns. Thirteen pairs of adjective words expressing emotion pairs such as like-dislike, beautiful-ugly, natural-unnatural, dynamic-static, warm-cold, gay-sober, cheerful-dismal, unstablestable, light-dark, strong-weak, gaudy-plain, hard-soft, heavy-light are modeled by 19-dimensional color array and $4{\times}3$ gray matrix in off-line. Once the query is presented in text format, emotion model-based query formulation produces the associated color array and gray matrix. Then, images related to the query are retrieved from the database based on the multiplication of color array and gray matrix, each of which is extracted from query and database image. Experiments over 450 images showed an average retrieval rate of 0.61 for the use of color array alone and an average retrieval rate of 0.47 for the use of gray matrix alone.

• Proceedings of the KSRS Conference
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• v.2
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• pp.695-697
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• 2006

Elshayal $Smart{\copyright}$ software is an almost First Arabian GIS $software{\copyright}$ which completely developed by Arabian developers team and independent of any commercial software package. The software current Features are View and Edit shape files, build new layers, add existing layers, remove layers, swap layers, save layers, set layer data sources, layer properties, zoom in & zoom out, pan, identify, selecting features, invert selection, show data table, data query builder, location query builder, build network, find shortest path, print map, save map image, copy map image to clipboard, save project map, edit move vertex, edit move features, snap vertexes, set vertex XY, move settings, converting coordinate system, applying VB script, copy selected features to another layer, move selected features to another layer, delete selected features, edit data table, modify table structure, edit map features, drawing new features, GPS tracking, 3D view, etc... The software expected Features are: Viewing raster image and image geo-referencing, read other map formats such as DXF Format and Tiger Line Format.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.61-63
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• 2005

Retreiving indoor scene reference image from database using visual information is important issue in Robot Navigation. Scene matching problem in navigation robot is not easy because input image that is taken in navigation process is affinly distorted. We represent probabilistic framework for the feature matching between features in input image and features in database reference images to guarantee robust scene matching efficiency. By reconstructing probabilistic scene matching framework we get a higher precision than the existing feaure-feature matching scheme. To construct probabilistic framework we represent each image as Gaussian Mixture Model using Expectation Maximization algorithm using SIFT(Scale Invariant Feature Transform).

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1997.11a
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• pp.33-36
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• 1997

This paper describes an image design process for product development based on human sensibility ergonomics.. The human sensibility about product image can be measured through some statistical methods and translated into product design factors by some mathematical inference logics. This results also can be presented by 3D computer graphic tools, In order to integrate the above processess, a image design process on human sensibility database. Human sensibility database is constructed with the relational ddta of some adjective words and design factors, The next step is to extract the design information from the human sensibility dataabase by fuzzy inference algouithm. This information is used for the input data for the graphic presentation. The final product can be modified according to the customer's requirement.

• Journal of the Korea Computer Industry Society
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• v.4 no.4
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• pp.613-624
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• 2003

This paper proposes a design for efficient and accurate retrieval of similar image subsequences using the multi-dimensional time warping distance as similarity evaluation tool in image sequence database after building of two indexing structures implemented with priority queue and suffix tree respectively. Receiving query image sequence, at first step, the proposed method searches the candidate set of similar image subsequences in priory queue index structure. If it can not get satisfied results, it retrieves another candidate set in suffix tree index structure at second step. The using of the low-bound distance function can remove the dissimilar subsequence without false dismissals during similarity evaluating process between query image sequence and stored sequences in two index structures.

• Journal of KIISE:Databases
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• v.36 no.5
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• pp.366-373
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• 2009

In this paper, we propose a similarity search algorithm for image databases. One of the central problems regarding content-based image retrieval (CBIR) is the semantic gap between the low-level features computed automatically from images and the human interpretation of image content. Many search algorithms used in CBIR have used the Minkowski metric (or $L_p$-norm) to measure similarity between image pairs. However those functions cannot adequately capture the aspects of the characteristics of the human visual system as well as the nonlinear relationships in contextual information. Our new search algorithm tackles this problem by employing new similarity measures and ranking strategies that reflect the nonlinearity of human perception and contextual information. Our search algorithm yields superior experimental results on a real handwritten digit image database and demonstrates its effectiveness.