A fast wavelet packet and PCA based image indexing and authentication method

The rapid growth in image databases is presenting new research challenges in wide range of areas that span image indexing, image retrieval, authentication, and recognition. This paper presents a new algorithm for image indexing and authentication. Although the combination of wavelet transform and principal components analysis has been used in some image processing areas but they have not been used for image indexing and authentication before. The proposed algorithm is based on the extraction of selected features of images using principal components analysis and wavelet packets. The proposed algorithm addresses three main concerns: (i) search accuracy; (ii) time efficiency; and (iii) storage requirements. We use wavelet packets to decompose the image to its fundamental subbands then we apply PCA method to extract the features of the images. The extracted features are used to create image signatures. We have tested our algorithm on the ORL Database of Faces (the AT&T laboratories Cambridge Database), PIE database, Caltech-UCSD Birds 200 and other miscellaneous images from different sources. We compared our results with two other methods [2] and [13] and found that our method retrieved the query image with 100% efficiency which significantly higher than that of method [13] and it is much faster than both methods.