• Science of Emotion and Sensibility
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• v.23 no.4
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• pp.21-32
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• 2020

The perception of a fashion product may vary depending on the texture and color of its material. Additionally, the product may appear differently in person versus on a digital screen. Therefore, in the present study, we sought to investigate the differences in visual sensibility evaluation between materials in person and on digital screens. In this study, three pairs of visual sensibility adjectives were tested for 60 samples selected as fashion materials. Fashion materials were divided into colors, embossings, and visual clarity categories. Results showed that each color had the same sense during in-person and digital evaluation. In terms of visual sensibility according to embossing, both in-person and digital evaluations of materials with embossings were found to have the same visual sense, whereas those without embossings looked different between in-person and digital evaluations. Assessments based on visual classification showed that both in-person and digital evaluations had the same sensibility. This study is meaningful in suggesting that when evaluating the visual sense of fashion material, the sensation for the digital screen versus in person may be different in some cases.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11a
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• pp.383-387
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• 2003

기존의 병리영상의 저장 및 관리, 공유를 위한 시스템이 수작업으로 이루어져 발생하는 문제점들을 보완하기 위한 방안으로 병리 영상의 전산화 및 대용량 자료를 표준화하여 보관하기 위한 시스템을 유방종양 영상을 사용하여 구축하였다. 다양한 유방종양 영상들을 질환별로 분류하고, 획득되어진 배율별로 구분하여 데이터 베이스를 구축하여 검색이 가능하도록 하였다. 비쥬얼 베이직을 이용하여 소프트제어를 개발하였으며, 검색되어진 영상에 대해 영상이 가지고 있는 컬러 및 질감특징값을 뽑아 영상의 객관적인 특성을 파악할 수 있도록 하였으며, 향후 다양하고 체계적인 병리 영상 세포은행을 구축하기 위 한 기반을 마련하였다.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.3
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• pp.27-35
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• 2002

A knowledge-based image retrieval technique is image searching methods using some features from the queried image. The materials in this study are automobile head lamps. The input data is composed of characters and images which have various pattern. The numbers, special symbols, and general letters are under the category of the character. The image informations are made up of the distribution of pixel data, statistical analysis, and state of pattern which are useful for the knowledge data. In this paper, we implemented a retrieval system for the scientific crime detection at traffic accident using the proposed multi knowledge-based image retrieval technique. The values for the multi knowledge-based image features were extracted from color and gray scale each. With this 22 features, we improved the retrieval efficiency about the color information and pattern information. Visual basic, crystal report and MS access DB were used for this application. We anticipate the efficient scientific detection for the traffic accident and the tracking of suspicious vehicle.