Color symbolism is considered a critical element in art and literature, yet determining the relationship between colors and words has remained largely subjective. This research presents a systematic methodology for quantifying the correlation between language and color. We utilize text-based image search, optical character recognition (OCR), and advanced image processing techniques to establish a connection between words and their corresponding color distributions in the CIELch color space. We generate a color dataset based on human cognition, and apply it for analysis of the literary works of poets associated with Imagism and Black Arts Movements. This helps uncover the characteristic color patterns and symbolic meanings of the movements with enhanced objectivity and reproducibility in literature research. Our work has the potential to provide a powerful instrument for a systematic, quantitative examination of literary symbolism, filling in the gaps in prior analyses and facilitating novel investigations of thematic aspects using color.