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Shape‐simplifying Image Abstraction
Author(s) -
Kang Henry,
Lee Seungyong
Publication year - 2008
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2008.01322.x
Subject(s) - abstraction , computer science , mean curvature flow , feature (linguistics) , curvature , simple (philosophy) , masking (illustration) , principal curvature , algorithm , image (mathematics) , flow (mathematics) , computer vision , artificial intelligence , mean curvature , mathematics , geometry , art , philosophy , epistemology , visual arts , linguistics
This paper presents a simple algorithm for producing stylistic abstraction of a photograph. Based on mean curvature flow in conjunction with shock filter, our method simplifies both shapes and colors simultaneously while preserving important features. In particular, we develop a constrained mean curvature flow, which outperforms the original mean curvature flow in conveying the directionality of features and shape boundaries. The proposed algorithm is iterative and incremental, and therefore the level of abstraction is intuitively controlled. Optionally, simple user masking can be incorporated into the algorithm to selectively control the abstraction speed and to protect particular regions. Experimental results show that our method effectively produces highly abstract yet feature‐preserving illustrations from photographs.