COLOR THEME EXTRACTION BASED ON THE T5 REGRESSION MODEL

This study employs a T5 regression model for color theme extraction, addressing the limitations of traditional methods, such as high subjectivity and low efficiency. Experimental results show that the model achieves a maximum accuracy of 0.416 and an average color difference of 28.546, generating harmonious and contextually appropriate color themes. Additionally, its performance across different color quantization sets is analyzed, offering new insights into the integration of AI and design industries, and paving the way for future applications in automated visual communication.