Image Similarity Analysis in Generative AI

• Published in: International Journal of Advanced Culture Technology(IJACT) Vol. 12; no. 4; pp. 208 - 214
• Main Authors: 최해린, 이현석
• Format: Journal Article
• Language: English
• Published: 국제문화기술진흥원 31.12.2024
• Subjects: 과학기술학; AI; Human Perception; SSIM; DALL-E; Structural Similarity; Visual Information Processing
• ISSN: 2288-7202; 2288-7318
• DOI: 10.17703/IJACT.2024.12.4.208

In Consciousness Explained, Daniel Dennett argued that consciousness is a phenomenon emerging from the complex flow of information in the brain, and to understand it, an objective approach is necessary. While AI is increasingly mimicking human functions, it is difficult to say that AI possesses consciousness similar to humans. However, consciousness is an essential factor for perception, but perception does not necessarily require consciousness. Therefore, this study aims to analyze how similar the way AI, particularly the DALL-E model developed by OpenAI, processes visual information is to the structure of human perception. In the study, new images were generated using the GPT-4 DALL-E model based on five sets of reference images, and the structural similarity between the generated images and the reference images was analyzed using SSIM (Structural Similarity Index Measure). The SSIM scores of the images generated by DALL-E based on the reference images ranged between 0.131 and 0.63. This confirmed that AI learned some degree of the visual patterns from the reference images. However, AI did not generate images that perfectly aligned with human perception, and images that contained complex shapes or fine textures recorded lower SSIM scores. Notably, the AI showed limitations in depicting human portraits, suggesting that AI’s perception system is simplified compared to the complexity of human perception structures. This study demonstrated that while the DALL-E model has potential in processing visual information, there remains a clear difference from the complex human perception system. These results suggest that AI still has limitations in mimicking the way humans process visual information, indicating a need for further in-depth research into the independent characteristics of AI perception in the future