Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/40496
Title: Identifying painters from color profiles of skin patches in painting images
Authors: Widjaja, I.
Leow, W.K. 
Wu, F.-C.
Issue Date: 2003
Source: Widjaja, I.,Leow, W.K.,Wu, F.-C. (2003). Identifying painters from color profiles of skin patches in painting images. IEEE International Conference on Image Processing 1 : 845-848. ScholarBank@NUS Repository.
Abstract: Research on digital analysis of painting images has received very little attention. The exact nature of scientific methods seems to be antithesis of art. Nevertheless, several papers have proposed methods to bridge this gap and have obtained interesting results. In fact, some art theorists have pointed out the usefulness of specific quantization features in the paintings. This paper presents a method for identifying painters using color profiles of skin patches in painting images. Various color models for representing the color profiles were explored. Various implementations of multi-class Support Vector Machine classifiers were compared. We found that a weighted combination of several Directed Acyclic Graph SVMs with Gaussian kernels gives the best classification performance.
Source Title: IEEE International Conference on Image Processing
URI: http://scholarbank.nus.edu.sg/handle/10635/40496
Appears in Collections:Staff Publications

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