The nature of statistical learning theory
The nature of statistical learning theory
Support Vector Machines for 3D Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bag-of-Words Vector Quantization Based Face Identification
ISECS '09 Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 02
Textile Image Segmentation Based on Semi-supervised Clustering and Bayes Decision
AICI '09 Proceedings of the 2009 International Conference on Artificial Intelligence and Computational Intelligence - Volume 03
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Semantic image classification, which is the process of categorizing images using pattern recognition technology, is very useful for image annotation, organization and retrieval. While the literature has focused on the classification of natural scene photographs or images, here we focus on the stylized textile images and this is totally a new area which is in the domain of artificial images. In this paper, we show that SIFT keypoint histograms perform much better than the traditional gray level co-occurrence matrix with the SVM classifier. Furthermore, we create a low-dimensional representation for each image using principle component analysis (PCA) method to the SIFT keypoint histograms and achieve a better result. To the best of our knowledge, this is the first time the SIFT feature histograms has been used to the classification of stylized textile images.