Layerwise Image Vectorization via Bayesain-Optimized Contour

Ghfran Jabour, Sergey Muravyov, Valeria Efimova

2025

Abstract

This work presents a novel method LIVBOC for complex image vectorization that addresses key challenges in path initialization, color assignment, and optimization. Unlike existing approaches such as LIVE, our method generates Bayesian-optimized contour for path initialization, which is then optimized using a customized loss function to align it better with the target shape in the image. In our method, adaptive selection of points and parameters for efficient and accurate vectorization is enabled to reduce unnecessary iterations and computational overhead. LIVBOC achieves superior reconstruction fidelity with fewer paths, and that is due to the path initialization technique, which initializes paths as contours that approximate target shapes in the image, reducing redundancy in points and paths. The experimental evaluation indicates that LIVBOC outperforms LIVE in all key metrics, including a significant reduction in L2 loss, processing time, and file size. LIVBOC achieves comparable results with just 100 iterations, compared to LIVE’s 500 iterations, while preserving finer details and generating smoother, more coherent paths. These improvements make LIVBOC more suitable for applications that require scalable, compact vector graphics, and computational efficiency. By achieving both accuracy and efficiency, LIVBOC offers a new robust alternative for image vectorization tasks. The LIVBOC code is available at https://github.com/CTLab-ITMO/LIVBOC.

Paper Citation

in Harvard Style

Jabour G., Muravyov S. and Efimova V. (2025). Layerwise Image Vectorization via Bayesain-Optimized Contour. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP; ISBN 978-989-758-728-3, SciTePress, pages 831-838. DOI: 10.5220/0013381000003912

in Bibtex Style

@conference{visapp25,
author={Ghfran Jabour and Sergey Muravyov and Valeria Efimova},
title={Layerwise Image Vectorization via Bayesain-Optimized Contour},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2025},
pages={831-838},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013381000003912},
isbn={978-989-758-728-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP
TI - Layerwise Image Vectorization via Bayesain-Optimized Contour
SN - 978-989-758-728-3
AU - Jabour G.
AU - Muravyov S.
AU - Efimova V.
PY - 2025
SP - 831
EP - 838
DO - 10.5220/0013381000003912
PB - SciTePress