A complete hand-drawn sketch vectorization framework
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.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
SketchGAN: Joint Sketch Completion and Recognition With Generative Adversarial Network
Hand-drawn sketch recognition is a fundamental problem in computer vision, widely used in sketch-based image and video retrieval, editing, and reorganization. Previous methods often assume that a complete sketch is used …
DecoderGenerative Adversarial NetworkRetrievalSketch Recognition+1Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting
Self-supervised learning has gained prominence due to its efficacy at learning powerful representations from unlabelled data that achieve excellent performance on many challenging downstream tasks. However supervision-fr…
Self-Supervised LearningTranslationSkeNa: Learning to Navigate Unseen Environments Based on Abstract Hand-Drawn Maps
A typical human strategy for giving navigation guidance is to sketch route maps based on the environmental layout. Inspired by this, we introduce Sketch map-based visual Navigation (SkeNa), an embodied navigation task in…
Visual NavigationCloud2Curve: Generation and Vectorization of Parametric Sketches
Analysis of human sketches in deep learning has advanced immensely through the use of waypoint-sequences rather than raster-graphic representations. We further aim to model sketches as a sequence of low-dimensional param…
VidSketch: Hand-drawn Sketch-Driven Video Generation with Diffusion Control
With the advancement of generative artificial intelligence, previous studies have achieved the task of generating aesthetic images from hand-drawn sketches, fulfilling the public's needs for drawing. However, these metho…
Video Generation