Image Latent Semantic Analysis for Face Recognition
نویسندگان
چکیده
In this paper, we propose a novel and effective image descriptor— Image Latent Semantic Analysis (ILSA) for extracting latent semantic features of face image. The features are obtained from a feature-image matrix, which obtains a wealth of information than the conventional image semantic and has a stronger expression and classification than the low-level features. The unique feature extraction by the ILSA can be better overcome the impact of some negative factors, such as the image quality fuzzy, illumination changes effect. The experiment results on the ORL and large-scale FERET databases show that proposed algorithms significantly outperforms other well-known algorithms in terms of recognition of recognition rate.
منابع مشابه
Face Recognition Based on Image Latent Semantic Analysis Model and SVM
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