M. Shneier, M. Abdel-Mottaleb, "Exploiting the JPEG Compression Scheme for Image Retrieval," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, no. 8, pp. 849-853, 1996.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....and some of the AC coefficients along the frequency bands [1] all the coefficients can be ranked according to their position inside the block. Depending on the application, the majority of the coefficients need not be used. When only content description [2] is required, partial decoding [3] can be performed to approximate the pixel information and construct indexing keys. The simplest way of doing so is to keep the first few coefficients and ignore the rest of them. This is referred to partial IDCT (Inverse Direct Cosine Transform) or partial decoding of JPEG images. Under this ....

....quality have little effect on the quality of the generated keys as texture based methods focus mainly on the distribution of pixel intensities within a relatively small neighbourhood and not over the whole image. The idea of performing texture indexing in the JPEG compressed domain is not new [3], however recent developments in computer hardware and necessity allow texture based keys to provide an interim solution to the retrieval problem and support future composite indexing keys. Thus, our approaches focus on improving the approximated image quality for key generation, and the accuracy ....

Shneier, M; Abdel-Mottaleb, M, "Exploiting the JPEG compression scheme for image retrieval", IEEE Trans on Pattern Analysis and Machine Intelligence, August 1996

....compression methods are developed in different domains including JPEG [10] 11] and JPEG 2000 [12] If one still wants to use these spatial based image retrieval systems to retrieve images, these compressed images should be first decompressed into uncompressed images. Shneier and Abdel Mottaleb [6] proposed a method that can retrieve images directly on JPEG images without decompressing JPEG images. However, the system can not apply their method directly on uncompressed images because their source images are limited in compressed images. Meanwhile, the system can not apply their method on ....

M. Shneier and M. Abdel-Mottaleb, "Exploiting the JPEG compression scheme for image retrieval," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 18, no. 8, pp. 849-853, Aug. 1996.

.... retrieval systems, either as combined features [20] or as seperate modules [26, 29, 14] Several other approaches to image retrieval have been suggested, including the use of transform coefficients as keys [40, 34, 32] using eigenfeatures [29, 36] and image retrieval from a compressed database [33, 40]. Locational information between objects in a scene has been incorporated into an image representation using 2D strings [31] and 2D Markov Models [22] A review on image retrieval can be found in [24, 30] 3 Object Process Methodology and Diagrams Any system has two major aspect: structure and ....

M. Shneier and M. Abdel-Mottaleb. Exploiting the jpeg compression scheme for image retrieval. IEEETransactions on Pattern Analysis andMachine Intelligence, 18(8):849--853, 1996.

....In these standards, a two dimensional DCT is applied to 8 8 blocks of pixels in the image. The 64 (8 8 = 64) coecients produced by the DCT are then quantized to provide the nal compression. DCTs have also been successfully used to generate keys for image retrieval from a large database [26] . Compared to other transforms, DCT has the advantages of having been implemented in a single integrated circuit because of its input independency, packing the most information into the fewest coecients for most natural images, and minimizing the blocklike appearance, called blocking artifact, ....

M. Shneier and M. Abdel-Mottaleb, \Exploiting the JPEG compression scheme for image retrieval," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, no. 8, pp. 849-853, 1996.

....to the proliferation of a number of compressed domain indexing techniques in the literature [12] Here, indexing is performed directly on the compressed data (see Fig. 2) Various indexing techniques have been proposed employing KarhunenLoeve transform (KLT) 13] discrete cosine transform (DCT) [14], and discrete wavelet transform (DWT) 15] A technique exploiting the directional property of DWT has been proposed in [9] Here, the histograms of different wavelet bands of the query image are employed as an index. The indexing techniques proposed in the literature generally assume that ....

M. Shneier and M. A. Mottaleb, "Exploiting the JPEG compression scheme for image retrieval," IEEE Transactions on Pattern Analysis and Machine Intelligence 18(8), 849-853, (Aug. 1996).

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M. Shneier, M. Abdel-Mottaleb, "Exploiting the JPEG Compression Scheme for Image Retrieval," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, no. 8, pp. 849-853, 1996.

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Shneier M,Abdel-Mottaleb M (1996) Exploiting the JPEGcompression scheme for image retrieval. IEEETrans PattAnal Mach Intell 18(8):849--853

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M. Shneier and M. Abdel-Mottaleb, "Exploiting the JPEG Compression Scheme for Image Retrieval," IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 18, no. 8, August 1996, pp. 849-853.

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