Automatic thread painting generation

TL;DR

This paper presents a novel optimization-based algorithm for generating high-quality thread paintings from images, improving upon greedy methods by utilizing chord space and error-diffusion sampling.

Contribution

It introduces the concept of chord space and an optimization approach to enhance thread painting quality over existing greedy methods.

Findings

Produces high-quality portraits, sketches, and cartoons

Outperforms greedy approaches in image similarity measures

Validated through user study

Abstract

ThreadTone is an NPR representation of an input image by half-toning using threads on a circle. Current approaches to create ThreadTone paintings greedily draw the chords on the circle. We introduce the concept of chord space, and design a new algorithm to improve the quality of the thread painting. We use an optimization process that estimates the fitness of every chord in the chord space, and an error-diffusion based sampling process that selects a moderate number of chords to produce the output painting. We used an image similarity measure to evaluate the quality of our thread painting and also conducted a user study. Our approach can produce high quality results on portraits, sketches as well as cartoon pictures.