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Precision Face Image Retrieval by Extracting the Face Features and Comparing the Features with Database Images

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Document pages: 7 pages

Abstract: An image retrieval system is a computer system for browsing, searching and retrieving images from a large database of digital images. Most traditional and common methods of image retrieval utilize some method of adding metadata such as captioning keywords, or descriptions to the images so that retrieval can be performed over the annotation words. Content-based face image retrieval is an existing technology for retrieving of images from large data base. Often, the retrieval results are not very satisfactory.The proposed method reduces the error and achieves better gain in face retrieval. By combining two orthogonal methods, results in improving of content-based face image retrieval.The proposed scheme uses two orthogonal methods named attribute-enhanced sparse coding and attribute embedded inverted indexing in order to reduce errors and achieve better extraction of images. These methods are used to improve the face retrieval in the offline stage such that the features of the image is extracted and then compared with the images present in the database.

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