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Cited by 297

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Manga colorization

Qu, Yingge, Wong, Tien-Tsin, Heng, Pheng-Ann·2006·ACM Transactions on Graphics

Abstract

This paper proposes a novel colorization technique that propagates color over regions exhibiting pattern-continuity as well as intensity-continuity. The proposed method works effectively on colorizing black-and-white manga which contains intensive amount of strokes, hatching, halftoning and screening. Such fine details and discontinuities in intensity introduce many difficulties to intensity-based colorization methods. Once the user scribbles on the drawing, a local, statistical based pattern feature obtained with Gabor wavelet filters is applied to measure the pattern-continuity. The boundary is then propagated by the level set method that monitors the pattern-continuity. Regions with open boundaries or multiple disjointed regions with similar patterns can be sensibly segmented by a single scribble. With the segmented regions, various colorization techniques can be applied to replace colors, colorize with stroke preservation, or even convert pattern to shading. Several results are shown to demonstrate the effectiveness and convenience of the proposed method.

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Crossref · 10.1145/1141911.1142017

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Metadata

Authors
Qu, Y., Wong, T.-T., & Heng, P.-A.
Venue
ACM Transactions on Graphics
Published
2006-07
Volume
25
Issue
3
Pages
1214-1220
ISSN
  • 0730-0301 (ISSN-L)
  • 1557-7368
OpenAlex
W2294092488
Cited by
297
References
1
FWCI
12.50
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Manga colorization. https://app.cochat.ai/papers/10.1145/1141911.1142017
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Qu, Y., Wong, T.-T., & Heng, P.-A. (2006). Manga colorization. ACM Transactions on Graphics. https://doi.org/10.1145/1141911.1142017

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.