• Journal of Convergence for Information Technology
• /
• v.11 no.11
• /
• pp.277-287
• /
• 2021

The purpose of this study is to establish a model that can quantitatively diagnose personal color. Representative color systems for personal colors have limitations in that it oversimplify personal color diagnosis types or it is difficult to distinguish objective differences between diagnosis types. To develop a brand new color system that enhances this, a PCCS color system capable of logical color was introduced and reclassified based on the four main properties of color. Twenty diagnostic types, which are more diverse than the existing color system were proposed and a quantitative method was used to evaluate the degree of harmony with a subject to find an optimized type of subject. The experimenter's individual competency and subjective intervention were minimized by devising a matrix in which a type suitable for the subject is derived when the coded evaluation result is substituted. Finally a quantitative diagnosis model of personal color consisting of three stages: property diagnosis, coding, and seasonal diagnosis was constructed. It can be seen that this will give diversity, reliability, and accuracy to the existing diagnostic methods.

• Cartoon and Animation Studies
• /
• s.39
• /
• pp.393-412
• /
• 2015

See and feel the emotion recognition is the image of a person variously changed according to the environment, personal disposition. Thus, the image recognition has been focused on the emotional sensibilities computer you want to control the number studies. However, existing emotional computing model is numbered and the objective is clearly insufficient measurement conditions. Thus, through quantifiable image Emotion Recognition and emotion computing, is a study of the situation requires an objective assessment scheme. In this paper, the sensitivity was represented by numbered sizes quantified according to the image recognition calculation emotion. So apply the principal attributes of the color image emotion recognition as a configuration parameter. In addition, in calculating the color sensitivity by applying a digital computing focused research. Image color emotion computing research approach is the color of emotion attribute, brightness, and saturation reflects the weighted according to importance to the emotional scores. And free-degree by applying the sensitivity point to the image sensitivity formula (X), the tone (Y-axis) is calculated as a number system. There pleasure degree (X-axis), the tension and position the position of the image point that the sensitivity of the emotional coordinate crossing (Y-axis). Image color coordinates by applying the core emotional effect of Russell (Core Affect) is based on the 16 main representatives emotion. Thus, the image recognition sensitivity and compares the number size. Depending on the magnitude of the sensitivity scores demonstrate this sensitivity must change. Compare the way the images are divided up the top five of emotion recognition emotion emotions associated with 16 representatives, and representatives analyzed the concentrated emotion sizes. Future studies are needed emotional computing method of calculation to be more similar sensibility and human emotion recognition.