A complete hand-drawn sketch vectorization framework

TL;DR

This paper introduces a comprehensive framework for automatic vectorization of hand-drawn sketches, effectively handling noise and complexity to produce simplified, accurate vector models suitable for creative workflows.

Contribution

It presents novel algorithms for line extraction, unbiased thinning, and optimized Bezier spline fitting, advancing the state-of-the-art in sketch vectorization.

Findings

Outperforms existing algorithms qualitatively and quantitatively.

Produces cleaner, more accurate vector representations of sketches.

Reduces control points in Bezier splines for simpler models.

Abstract

Vectorizing hand-drawn sketches is a challenging task, which is of paramount importance for creating CAD vectorized versions for the fashion and creative workflows. This paper proposes a complete framework that automatically transforms noisy and complex hand-drawn sketches with different stroke types in a precise, reliable and highly-simplified vectorized model. The proposed framework includes a novel line extraction algorithm based on a multi-resolution application of Pearson's cross correlation and a new unbiased thinning algorithm that can get rid of scribbles and variable-width strokes to obtain clean 1-pixel lines. Other contributions include variants of pruning, merging and edge linking procedures to post-process the obtained paths. Finally, a modification of the original Schneider's vectorization algorithm is designed to obtain fewer control points in the resulting Bezier splines. All the proposed steps of the framework have been extensively tested and compared with state-of-the-art algorithms, showing (both qualitatively and quantitatively) its outperformance.