Modeling the Perception of Visual Complexity in Texture Images and Painting Images

• 資料種別: 博士論文
• タイトル: Modeling the Perception of Visual Complexity in Texture Images and Painting Images
• 著者・編者: Guo, Xiaoying
• 著者標目: Guo, Xiaoying
• 並列タイトル等: テクスチャー画像および絵画に対する複雑さの知覚モデルの構築
• 授与機関名: 広島大学(Hiroshima University)
• 授与年月日: 2013-09-25
• 報告番号: 甲第6232号
• 学位: 博士(工学)
• 本文の言語コード: eng
• 件名標目: visual complexity; texture images; painting images; kansei engineering; affective engineering; image features; support vector machine; color complexity; understandability.
• NDC: 007
• 対象利用者: 一般
• 一般注記: type:text; This thesis devotes to building a relationship between human visual complexity perception and objective image features. Visual complexity of images is a worth-well investigation. It has a wide range of applications from computer science (emotion semantic image retrieval, digital watermarking and image analysis, etc.) to arts (the design of product surface, wallpapers, painting appreciation and selection, etc.). Various methods for computing image complexity have been developed depending on different applications, such as information theory, fractal dimension, quad tree method, etc. However, these measures are not sufficiently related to human visual perception of complexity. Intuitively, visual complexity is influenced by various factors perceived by humans from the image, not directly related to simple objective measures like distribution of spatial frequencies.……
• 記録形式（IMT）: application/pdf
• オンライン閲覧公開範囲: インターネット公開
• 著作権情報: Copyright(c) by Author
• 連携機関・データベース: 国立情報学研究所 : 学術機関リポジトリデータベース（IRDB）（機関リポジトリ）; https://irdb.nii.ac.jp
• 提供元機関・データベース: 広島大学 : 広島大学学術情報リポジトリ

目次

http://ir.lib.hiroshima-u.ac.jp/files/public/3/35133/20141016204220851334/k6232_3.pdf fulltext

http://ir.lib.hiroshima-u.ac.jp/files/public/3/35133/20181114101613747241/k6232_1.pdf fulltext

http://ir.lib.hiroshima-u.ac.jp/files/public/3/35133/20181114101614334212/k6232_2.pdf fulltext