配色調查樣本之色彩交錯搭配關係研究

The Intersecting Matching Relationship of Color Coordinate Census Samples

當人類眼睛觀看同時存在的幾個色彩時，不會僅對各單一色彩發生感覺，而是同時對所有相關色彩，共同產生「色相對比」、「彩度對比」、「明度對比」三種「色彩對比」的色彩感覺。亦即根據這些色彩的「色相相互關係之對比」、「彩度相互關係之對比」、「明度相互關係之對比」，來感知這些色彩的互相搭配結果。因配色調查時，都會結合許多個特性相同的「實驗樣本」組成「配色調查樣本」。所以「配色調查樣本」的組成，不僅涉及單個「實驗樣本」自身的「色相相互關係」、「彩度相互關係」、「明度相互關係」的相互搭配關係，同時也涉及不同「實驗樣本」之間的不同「色相相互關係」的相互搭配關係，與不同「彩度相互關係」的相互搭配關係，與不同「明度相互關係」的相互搭配關係。同時也會涉及單個「實驗樣本」的「色相相互關係」、「彩度相互關係」、「明度相互關係」相互搭配結果，與同一群集其他單個「實驗樣本」的「色相相互關係」、「彩度相互關係」、「明度相互關係」相互搭配結果之間的相互組成關係。 以上交錯混雜的盤疊關係，若不經系統化的組織整理，將很難有效釐清。所以本文研究目的，是試圖建立一套系統化的「配色調查樣本」組成模式，不僅能適當的導入任何配色調查目的，又能完全符合上述的複雜色彩搭配關係。只是礙於研究內容篇幅過大，所以本文僅進行前半部分的研究，即“配色調查樣本之色彩交錯搭配關係研究＂。研究步驟如下：1.設定色彩樣本2.排列各「色相相互關係」、「彩度相互關係」、「明度相互關係」，再交錯搭配成「全部實驗樣本群集」3.利用「分裂式階層群集法」，分裂成不同配色關係特性的「實驗樣本群集」4.抽取特定條件群集的所有「實驗樣本」5.最後組成「配色調查樣本」。

When human see several colors at the same time, they not only perceive those isolated colors, but synchronize hue, chroma, and value contrasts. It means according to the mutual contrasts of hue, chroma, and value, human perceive the results of colors coordinates. In color coordinate census, we comprise color coordinate census samples from experimental samples which have the same characters. Each sample above not merely involves mutual relationship of hue, chroma, and value by itself, but also other experimental samples with mutual relationship of different hue, chroma, and value. Meanwhile it involves the composition results of intersecting matching relationship with others in the samples group. Above mentioned complicated relationship needs to organize systematically, or it will be ambiguous. In this respect, the purpose of this study is to build a systematic organization model of 'color coordinate census samples'; it can both accommodate the purpose of color coordinate census properly and correspond to above complicated relationship. Due to limited space, this study builds only the first part of the research, 'The intersecting matching relationship of color coordinate census samples'. This study involves five steps as follows: 1. To set up the color samples. 2. To rank' hue inter-relationship', 'chroma inter-relationship', and 'value inter-relationship', then gain 'all experimental samples groups' by intersecting matching. 3. To separate 'experimental samples groups' of differential matching relationship characters by 'Hierarchical Partitioning Clustering'. 4. To pull out all the 'experimental samples' of specific condition groups. 5. To comprise 'color coordinate census samples'.