MangaWall: Generating manga pages for real-time applications

Recent advances in non-photorealistic rendering provide the best convenience for automatic image to manga conversion. However, we are facing a dilemma that the fine-grained manga conversion algorithms always involve computation intensive processes (e.g. image over-segmentation, brute-force feature matching, and energy optimization), which make it inapplicable to real-time applications. On the other hand, commercial manga Apps available for smart phones usually rely on simple edge detection and halftoning or hatching. Although the processing can be finished in several seconds, the conversion quality is not satisfactory yet. In this paper, we propose MangaWall to automatically convert and organize photos into manga pages. Our goal is to establish a lightweight manga rendition framework as well as generate high-quality images. To achieve this, the manga structure is enhanced by flow-based DoG operation and image vectorization. A multi-layer tone mapping and contrast-aware halftoning method is then proposed to render the manga-like screentone patterns. Besides, for multi-image input, a full binary tree-based layout representation is employed to efficiently organize manga images onto the same page canvas. Our MangaWall can be applied to real-time applications. It takes less than 0.7 second to convert a 1024 × 768 image into manga on Laptop PC.