A Decision Tree Based Image Enhancement Instruction System for Producing Contemporary Style Images
學年 104
學期 2
發表日期 2016-07-17
作品名稱 A Decision Tree Based Image Enhancement Instruction System for Producing Contemporary Style Images
作品名稱（其他語言）
著者 M. L. Wu; C. S. Fahn
作品所屬單位
出版者
會議名稱 International Conference on Human-Computer Interaction
會議地點 Toronto, Canada
摘要 In this paper, we have proposed an image enhancement method by contemporary aesthetics criteria, which enables computers to produce visually favorable images automatically. The contemporary aesthetics criteria is obtained through data mining algorithms such as decision tree, support vector machine, and neural networks. In order to make computers adjust the images automatically to make them match the contemporary aesthetics criteria, the tree-based classification method is proposed for enhancement instructions. Our proposed system finds the reasons in the tree why an input image is not perceptually favorable and give improvement instructions accordingly. The training features are based on enhancement instructions, such as color component, saturation, sharpness, and so on. Preprocessing methods are also proposed for a more efficient labeling and better accuracy for image classification. The training samples are from both contemporary style high aesthetics quality images and those are not, which more than 15,000 training samples are used. The accuracy of our proposed method is above 95 %. The experimental result shows our system can give users or computers appropriate enhancement instruction efficiently.
關鍵字 Professional photographing;Computational aesthetics;Autonomous photographing;Data mining;Image retouching;Image enhancement
語言 en_US
收錄於
會議性質 國際
校內研討會地點 無
研討會時間 20160717~20160722
通訊作者
國別 CAN
公開徵稿
出版型式
出處
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/120094 )

SDGS 尊嚴就業與經濟發展,產業創新與基礎設施