A Deep Learning-Based High-Resolution Illusion Poster Generation System Using Large-Scale Image Mosaic Reconstruction from Video Frames

Author(s)	Mr. Virendra Madhukar Deshpande, Dr. Manisha Bharathi
Country	India
Abstract	This research presents a deep learning-based system for generating a high-resolution illusion poster using 10,000 images that reconstruct a target image when viewed from a distance. The proposed method utilizes VLC Media Player to convert movies into frames stored as JPEG files and produces nearly 3,000,000 unique images. A hybrid deep learning approach using Convolutional Neural Networks (CNN), AdaptiveAvgPool2d, RGB similarity, and feature matching is proposed for image selection and poster reconstruction. The generated poster produces an optical illusion where individual images are visible at close range, while the original target image becomes visible when zoomed out. The system improves visual accuracy, scalability, and reconstruction quality for large mosaic-based image generation.
Keywords	Illusion Poster, Deep Learning, AdaptiveAvgPool2d, VLC Media Player, Feature Matching, RGB Similarity
Field	Computer Applications
Published In	Volume 8, Issue 3, May-June 2026
Published On	2026-05-29
DOI	https://doi.org/10.36948/ijfmr.2026.v08i03.79883

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