Applications of Colour Harmony on Apparel Colour Combinations: Taking Images of Taiwanese Young Adults as an Example

• Main Authors: I-HAN LIU, 劉憶涵
• Other Authors: LI-CHEN OU
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/bt28sj

碩士 === 國立臺灣科技大學 === 色彩與照明科技研究所 === 106 === With the rise of social media and e-commerce, the frequency of digital images being viewed everyday has greatly increased. As an important media for fashion, the amount of fashion information received by people from websites and social platforms is gradually larger than that of traditional newspapers or magazines. In this research, psychophysical experiments were conducted to investigate the application of colour harmony on apparel colour combinations. By analysizing the experimental results, hoping this research can bring some suggestions for those who have problems picking colour for apparel. This research consists of two experiments. The first experiment investigated colour combinations for apparel in female images; the second experiment focused on male images. The experimental display was well controlled and measured to manipulate colours of the shirts, trousers and skintone respectively. The same set of color combinations was used for each of the two garment styles. The categorical judgement method was used for data analysis. The experimental data was used to verify existing color harmony models. The results of the first experiment show that gender had significant effects on all scales; the style had significant effects on all scales; the color harmony model proposed by Ou and Luo did not perform well for the data obtained in the present study; the Huang model performed better. The results of second experiment show that there was high correlation between the four scales. Gender had significant effects on some scales. The style had significant effects on some scales; the color harmony model proposed by Ou and Luo did not perform well for the data obtained in the present study; the Huang model performed better, both of two models were better than the first experiment.