An information-based color feature representation and its application in detecting adult images
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Author(s)
Wang, SL
Liew, WCA
Griffith University Author(s)
Year published
2011
Metadata
Show full item recordAbstract
For many image classification tasks, color histogram is usually employed as an important "signature" to describe the color distribution of the image and infer the image content. However, most traditional color histograms cannot achieve satisfactory results in many image classification systems. In order to improve the accuracy and reduce the computational complexity of the classification task, an information-based color feature representation is proposed in this paper. The mutual information between the feature and the class label is adopted to evaluate the discriminative power of the feature. A novel quantization scheme is ...
View more >For many image classification tasks, color histogram is usually employed as an important "signature" to describe the color distribution of the image and infer the image content. However, most traditional color histograms cannot achieve satisfactory results in many image classification systems. In order to improve the accuracy and reduce the computational complexity of the classification task, an information-based color feature representation is proposed in this paper. The mutual information between the feature and the class label is adopted to evaluate the discriminative power of the feature. A novel quantization scheme is presented, which removes the redundant color components and combines the adjacent components together to generate a new feature to maximize the discriminative ability. An iterative algorithm is performed to derive the color space quantization and color feature generation. In order to illustrate the effectiveness of the proposed color representation, a specific image classification task, i.e., differentiating the adult images from benign ones, is employed. Experimental results show that our color feature achieves better classification performance and better efficiency compared with the traditional color histogram.
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View more >For many image classification tasks, color histogram is usually employed as an important "signature" to describe the color distribution of the image and infer the image content. However, most traditional color histograms cannot achieve satisfactory results in many image classification systems. In order to improve the accuracy and reduce the computational complexity of the classification task, an information-based color feature representation is proposed in this paper. The mutual information between the feature and the class label is adopted to evaluate the discriminative power of the feature. A novel quantization scheme is presented, which removes the redundant color components and combines the adjacent components together to generate a new feature to maximize the discriminative ability. An iterative algorithm is performed to derive the color space quantization and color feature generation. In order to illustrate the effectiveness of the proposed color representation, a specific image classification task, i.e., differentiating the adult images from benign ones, is employed. Experimental results show that our color feature achieves better classification performance and better efficiency compared with the traditional color histogram.
View less >
Journal Title
Journal of Shanghai Jiaotong University (Science)
Volume
16
Issue
4
Copyright Statement
© 2011 Shanghai Jiao Tong University Press. This is an electronic version of an article published in Journal of Shanghai Jiaotong University (Science), Volume 16, Number 4 (2011), 395-401. Journal of Shanghai Jiaotong University (Science) is available online at: http://www.springerlink.com/ with the open URL of your article.
Subject
Image processing
Maritime engineering