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Data Compression and Hiding Using Vector Quantization Techniques


Affiliations
1 Department of Information Technology, Sri Ramakrishna Institute of Technology, Pachapalayam, Coimbatore-641010, Tamilnadu, India
     

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Embedding of useful information in a host signal without any loss of host information is need for copyrights protection. Customer identification can be embedded directly into multimedia files, this leads to a number of specific requirements with respect to robustness, transparency and complexity. In early data hiding can be done by difference expansion, histogram shifting, and Spatial-domain and frequency-domain techniques. Which lead to high PSNR values and more robust imperceptibility, avoid such a kind of issue this paper concentrate on vector quantization technique which can split and compress the data into smaller groups and are embedded into the multimedia pixels. This VQ method enables for effective pixel utilization and retrieves the content without any loss of original pixels. This kind of VQ is based on indices; the data content can be mapped into many to one form.

Keywords

Data Hiding, Stenography, Water Marking, Vector Quantization, Copyright Protections.
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  • Data Compression and Hiding Using Vector Quantization Techniques

Abstract Views: 252  |  PDF Views: 4

Authors

A. Suresh
Department of Information Technology, Sri Ramakrishna Institute of Technology, Pachapalayam, Coimbatore-641010, Tamilnadu, India

Abstract


Embedding of useful information in a host signal without any loss of host information is need for copyrights protection. Customer identification can be embedded directly into multimedia files, this leads to a number of specific requirements with respect to robustness, transparency and complexity. In early data hiding can be done by difference expansion, histogram shifting, and Spatial-domain and frequency-domain techniques. Which lead to high PSNR values and more robust imperceptibility, avoid such a kind of issue this paper concentrate on vector quantization technique which can split and compress the data into smaller groups and are embedded into the multimedia pixels. This VQ method enables for effective pixel utilization and retrieves the content without any loss of original pixels. This kind of VQ is based on indices; the data content can be mapped into many to one form.

Keywords


Data Hiding, Stenography, Water Marking, Vector Quantization, Copyright Protections.