<![CDATA[The increasing use of visual media in university admissions highlights the need for systematic evaluation of promotional poster design. However, existing assessments are largely subjective and lack measurable indicators. This study aims to analyze the visual and textual characteristics of a university admission poster using a computational approach. A quantitative–descriptive visual case study was conducted using Python-based image processing, including color histogram analysis, dominant color extraction, grayscale density measurement, edge detection, and Optical Character Recognition (OCR). The results show a grayscale density of 140.31, an edge density ratio of 9.16%, and a text area ratio of 11.85%, indicating moderate visual complexity and structured layout organization. The dominant color palette and OCR results (169 words; 1,179 characters) reflect a relatively high informational load. These findings represent visual features associated with communicative design and are interpreted as theoretical proxies rather than direct measures of communication effectiveness. The study provides a computational, theory-informed framework for analyzing promotional poster design in higher education contexts.]]>
Copyrights © 2026
