研究生: |
陳唐羽 Tang-Yu Chen |
---|---|
論文名稱: |
紋理屬性空間之研究 Study of texture-based perceptual space |
指導教授: |
陳鴻興
Hung-Shing Chen |
口試委員: |
陳建宇
Chien-Yue Chen 孫沛立 Pei-Li Sun 林宗翰 Tzung-Han Lin |
學位類別: |
碩士 Master |
系所名稱: |
電資學院 - 光電工程研究所 Graduate Institute of Electro-Optical Engineering |
論文出版年: | 2015 |
畢業學年度: | 103 |
語文別: | 中文 |
論文頁數: | 75 |
中文關鍵詞: | 樣本集 、紋理屬性空間 、對比度 、複雜度 、精細度 |
外文關鍵詞: | altas, texture-based perceptual space, contrast, complexity, fineness |
相關次數: | 點閱:377 下載:1 |
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一套好的標準系統應包括數學模型與樣本集,它可以幫助工程師與設計師彼此互相溝通,提高開發的效率,另一方面由於將產品屬性以準確測量定義,這些資料可直接用來進行品管,以確保生產品質。在色彩工程領域中,已經有成熟的標準系統,例如:CIE標準色彩體系統利用配色實驗將人的色彩感知量化,適用於需要精確控制顏色的場合;孟賽爾色彩體系利用大量的心理物理實資料驗建構出均等色彩空間,並搭配色票的表示方法,使顏色的表達更為直覺。
隨著材料的多樣性、物體外貌的研究越來越多。除了物體的顏色之外,物體的表面紋理是物體外貌的重要屬性之一。本研究利用三維列印技術,製作16個紋理樣本(4種顆粒形狀 × 4種數量密度),並設計一套搭配成對比較法與主成分分析技術的紋理屬性研究方法。本研究將分析紋理屬性之間的相關性,依此建構出一套紋理屬性空間,此空間的三個座標軸分別為:對比度、複雜度以及精細度。
A good standardized system includes mathematics model and altas, It helps designers and engineers communicate with each other, and improves Research & Development efficiency. On the other hand, product attributes will be accurately measured, and the measuring data is applied to quality control. Therefore, designers and engineers can ensure products quality. There are mature standardized system in the field of color engineering, for example, CIE standard colorimetric system which utilized color matching experiment to quantize human perceptual color. It is fit for accurately controlling condition. And Munsell color system which applied psychophysical experiment to establish uniform color space and color sample. It visually expresses color.
More object appearance researches are proceeded due to the increasing diversity of materials. Not only color is one of the important appearance attributes, but also the texture is a kind of important appearance attribute. In this study, we made the 16 texture samples (4 particle shape × 4 number density) outputted by 3D printing technology, and designed an analytical method to investigate texture attributes by pair comparison and principal component analysis. This study analyzed the relationship among sample texture attributes and built up a texture-based perceptual space including contrast, complexity, and fineness.
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