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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yuejian Guo Hong Li Wei Zhang Yao Xiang |
| Copyright Year | 2008 |
| Description | Author affiliation: Sch. of Archit. Eng., Hunan Univ., Changsha (Wei Zhang) || Sch. of Inf. Sci. & Eng., Central South Univ., Changsha (Yuejian Guo; Hong Li; Yao Xiang) |
| Abstract | At present, most color transfer algorithms are based on single source image, failing to meet reference color demand of object image. This paper proposes a multi-source color transfer algorithm based on multi-labeled decision tree. At first, we define an image as a multi-labeled set since it contains multiple objects. Then every source image is divided into several sub-images to form the training samples for the decision tree. Through extracting color and texture features from sub-image, training dataset is formed and the corresponding label set is obtained by amended K-mean clustering. After that, a multi-labeled decision tree is constructed using SCC_SP. Finally, color transfer is performed on object image based on its predicted label set by the built tree. Experiment results demonstrate that the proposed algorithm works well on multi-source color transfer, making up the shortage of color transfer based on single source image. |
| Starting Page | 820 |
| Ending Page | 825 |
| File Size | 469858 |
| Page Count | 6 |
| File Format | |
| ISBN | 9780769533988 |
| DOI | 10.1109/ICYCS.2008.30 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-11-18 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | multi-labeled multi-source Color Electronic mail Data mining classification Information science Image segmentation decision tree Layout Clustering algorithms Computer architecture Color transfer Decision trees Classification tree analysis |
| Content Type | Text |
| Resource Type | Article |
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