Exploiting the JPEG compression scheme for image retrieval

Shneier, Michael O.; Abdel-Mottaleb, Mohamed

doi:10.1109/34.531805

Cited by 117 publications

(31 citation statements)

References 9 publications

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“…Currently, the compressed domain-based indexing method greatly depends on their compression techniques. DCT-domain based indexing techniques extract features from the DCT coefficients [2]. Whereas, wavelet domain-based retrieval systems regard significant wavelet magnitudes as features [3].…”

Section: Introductionmentioning

confidence: 99%

Direct image retrieval in JPEG and JPEG2000

Law

Siu

2005

IEEE International Conference on Image Processing 2005

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Images are often compressed using JPEG or JPEG2000. Many retrieval systems operated in either uncompressed or compressed domains have been proposed. However, retrieving in multiple domains typically involves full decompression for feature analysis in spatial domain. Common features in different domains are thus worth of investigation for direct image indexing. By employing a common subband filtering model, outputs from JPEG and JPEG2000 can be compared directly without having a full decompression. Despite of high compression, similar translation and rotation invariant features can be extracted from these two domains. Simulation results reveal that JPEG and JPEG2000 compressed images can be searched from one another irrespective of the compression ratio. Our experimental studies confirm that retrieval in multiple domains is possible without a full decompression.

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Section: Introductionmentioning

confidence: 99%

Direct image retrieval in JPEG and JPEG2000

Law

Siu

2005

IEEE International Conference on Image Processing 2005

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“…Some techniques both in 2D and in 3D are based on coefficients yielded by compression transforms like the cosine [28] or wavelet transform e.g. in [17].…”

Section: Projection Based Techniquesmentioning

confidence: 99%

3D zernike descriptors for content based shape retrieval

Novotni

Klein

2003

Proceedings of the Eighth ACM Symposium on Solid Modeling and Applications

255

202

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Content based 3D shape retrieval for broad domains like the World Wide Web has recently gained considerable attention in Computer Graphics community. One of the main challenges in this context is the mapping of 3D objects into compact canonical representations referred to as descriptors, which serve as search keys during the retrieval process. The descriptors should have certain desirable properties like invariance under scaling, rotation and translation. Very importantly, they should possess descriptive power providing a basis for similarity measure between three-dimensional objects which is close to the human notion of resemblance.In this paper we advocate the usage of so-called 3D Zernike invariants as descriptors for content based 3D shape retrieval. The basis polynomials of this representation facilitate computation of invariants under the above transformations. Some theoretical results have already been summarized in the past from the aspect of pattern recognition and shape analysis. We provide practical analysis of these invariants along with algorithms and computational details. Furthermore, we give a detailed discussion on influence of the algorithm parameters like type and resolution of the conversion into a volumetric function, number of utilized coefficients, etc. As is revealed by our study, the 3D Zernike descriptors are natural extensions of spherical harmonics based descriptors, which are reported to be among the most successful representations at present. We conduct a comparison of 3D Zernike descriptors against these regarding computational aspects and shape retrieval performance.

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“…According to [43], an improved denoising algorithm is recognized by a high PSNR or a lower M SE. In agreement with this, the results of the proposed systems with high PSNR prove that they are an improved version.…”

Section: Cover Imagesmentioning

confidence: 99%

Multiple Watermarking Scheme for Image Authentication and Copyright Protection using Wavelet based Texture Properties and Visual Cryptography

Radharani¹,

Valarmathi²

2011

IJCA

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Advancement in communication medium is producing large volume of digital information which needs to be protected. Watermarking is a technique that is used to hide secret signal into digital signal in a manner that does not reduce overall quality of the original signal. In relation to digital image watermarking, another area that is drawing attention is the multiple watermarking, where more than one watermark is embedded into single multimedia object. M ultiple watermarks are normally proposed as a method to provide extra security to an image by embedding two or more secret messages into the cover image. In the present research work, the concept of multiple watermarking is used to hide both copyright and authentication information into a color image. For this purpose a wavelet transformation based on texture properties and secret sharing us ing visual cryptography is used. Experimental results indicate that the proposed watermarking scheme is highly robust and does not degrade the original signal.

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Exploiting the JPEG compression scheme for image retrieval

Cited by 117 publications

References 9 publications

Direct image retrieval in JPEG and JPEG2000

Direct image retrieval in JPEG and JPEG2000

3D zernike descriptors for content based shape retrieval

Multiple Watermarking Scheme for Image Authentication and Copyright Protection using Wavelet based Texture Properties and Visual Cryptography

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