Title
Simulating Chalk Art Style Painting
Abstract
Different kinds of illustrations and artistic imagery can be generated or simulated through the nonphotorealistic rendering (NPR) technique. However, designing and simulating new NPR artistic styles remains extremely challenging. Chalk art style is a very famous artistic work all over the world, and few algorithms have been put forward to illustrate this style. This paper presents a novel NPR technique which generates a chalk art drawing from a 2D photograph automatically. We aim at obtaining a set of lines surface with coarse appearance and generating stroke textures of the real chalk painting. Firstly, the edge of the source image is extracted by difference-of-Gaussian filter method. To simulate chalk painting's lines, image diffusion and enhancement techniques are proposed to produce coarse and rough lines. Secondly, we developed an improved line integral convolution and dilation operation methods to produce the chalk stroke texture. Finally, the edge image, stroke texture image and color image will be mapped to another background image to generate the chalk art drawing. Experimental results are presented to show the effectiveness of our method in producing the color chalk stylistic illustrations, and the methods can simulate the characters of the real chalk art painting. The proposed method of this paper will enlarge the research and application fields of NPR. Meanwhile, it provides a tool for the user to create chalk art paintings via computers even without painting skill.
Year
DOI
Venue
2017
10.1142/S0218001417590261
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
Keywords
Field
DocType
Nonphotorealistic rendering, chalk art, edge detection, stroke texture, image mergence
Computer graphics (images),Edge detection,Painting,Rendering (computer graphics),Mathematics,Line integral convolution,Color image,Art painting
Journal
Volume
Issue
ISSN
31
12
0218-0014
Citations 
PageRank 
References 
0
0.34
13
Authors
5
Name
Order
Citations
PageRank
Wenhua Qian126.11
Dan Xu220152.67
Zheng Guan302.03
Kun Yue425840.11
Yuanyuan Pu502.37