{"pk":49853,"title":"A Visual Complexity Measurement Method Based on Monte Carlo Sampling","subtitle":null,"abstract":"Conventional visual complexity measurement faces challenges in efficiency, accuracy, and alignment with human perception. To address these, this paper presents a novel Monte Carlo-based method for visual complexity measurement, the random line segment width sampling algorithm (RLSWSA). RLSWSA employs local stochastic sampling for efficient estimation of symbol perimeter complexity. By discarding global scanning in favor of local sampling, RLSWSA significantly enhances computational efficiency while maintaining high accuracy and robustness. Experimental results show rapid convergence with just 24 samples, yielding high consistency with traditional methods (correlation coefficient > 0.9). Furthermore, RLSWSA's Spearman correlation with human subjective ratings is 0.74, demonstrating its strong correlation with human perceptual complexity. This study offers an efficient and reliable solution for rapid symbol visual complexity calculation, with strong potential for applications like symbol recognition and design optimization.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"Computer Science; Psychology; Aesthetics; Representation; Computational Modeling"}],"section":"Papers with Poster Presentation","is_remote":true,"remote_url":"https://escholarship.org/uc/item/5kv4h6p0","frozenauthors":[{"first_name":"Sihan","middle_name":"","last_name":"Wang","name_suffix":"","institution":"Jiangnan University","department":""},{"first_name":"Ruimin","middle_name":"","last_name":"Lyu","name_suffix":"","institution":"Jiangnan University","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2025-01-01T13:00:00-05:00","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/49853/galley/37815/download/"}]}