As material living standards improve, consumers now seek literary and artistic products that offer both function and visual appeal. Attention is increasingly focused on design, form, and aesthetics, making purely functional items less attractive. However, current research on image aesthetics often overlooks the role of human visual saliency and attention in beauty perception, limiting evaluation performance. To address this, the study proposes a novel method that mirrors the brain's processing of visual stimuli. It introduces two algorithms: one based on compositional edge features and another using weakly supervised learning for aesthetic classification through attention mechanisms. By combining visual saliency with aesthetic evaluation, the approach better aligns with human perception and improves assessment accuracy. This method enhances understanding of aesthetic judgment and supports the development of more appealing designs, offering a valuable framework for evaluating the visual quality of literary and artistic products in today's design-conscious market.
