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Digital Video And Hdtv Algorithms And Interfaces

Secured Reversible matrix embedding based on dual image using Integer wavelet and Arnold Transform

JPEG is one of the widely used image format. As like other image formats, JPEG has its own special bytes called JPEG markers or metadata that gives relevant information about the image. In applications such as watermarking, image theft identification and digital forensics, where some kind of confidential information is embedded into the image either for copyright protection or image authentication. Usually this embedding is done on DCT coefficients. But with the use of quantization technique and compression nature of JPEG, the extraction/recovery of embedded data may not be possible all the times. A solution to this is to use quantized DCT coefficients for embedding. In order to decode the compressed data into quantized DCT coefficients, the encoding method used and also the type of chroma-subsampling used are to be known. This information is stored in the JPEG marker segment along with other relevant information. This paper detailed about the various types of JPEG markers and has shown experimental results. This will help young researchers to get the basic idea about the JPEG metadata.

JPEG Metadata: A complete study

Interpolation-based reversible data hiding in the transform domain for fingerprint images

As the technology is reaching its next level day by day, the concerns over information or data security are also creeping up. Biometric systems have been widely used in many real-world applications in order to provide more security to the data. Iris recognition system has become a widely used system for human identification from the last few decades. In this paper, an efficient iris recognition system is proposed where iris localization is carried out by first finding the pupil-iris boundary using the connected component analysis approach. And then by considering the pupil center as the reference point, it traverses through the virtual outer boundary to detect the iris-sclera boundary. After applying normalization on the iris region, the iris region is partitioned into non-overlapping blocks. Further, a combination of integer wavelet transform (IWT) with log energy entropy (LEE) is applied on each block to extract the unique iris code as the feature vector. The experiments have been conducted using the multimodal biometric database, SDUMLA-HMT. The proposed system has succeeded in achieving a low false acceptance rate and a very low false rejection rate. Also, the uniqueness of the iris patterns is evaluated in terms of degrees of freedom and is found to be a promising one.

Iris Recognition Using Integer Wavelet Transform and Log Energy Entropy

Reversible data hiding is art of concealing secret information such that cover media and secret information are both recovered without any information loss. In this paper high frequency sub-bands of integer wavelet transform are used for data embedding. All coefficients are used for embedding and to improve the security the embedding is carried out in frequency domain using spiral, sequential and random embedding method. The main objective of this research is to hide the maximum data with minimal distortion and to attain reversible hiding phenomenon both in cover and secret image. The experimental result shows the improved capacity, imperceptibility and complete reversibility attained on standard and medical images. The parameter of robustness has not been vastly studied for reversible data hiding and an attempt is made to check the same for basic attacks and results shows that it can withstand geometrical attack.

Reversible data hiding methods in integer wavelet transform

In todayâ€™s internet world, all the data are represented and stored in digital form. Almost any entity in this world can be represented digitally, rangingÂ from simple text to complex multimedia work. Now, the challenge is to claim the ownership and prevent theft of oneâ€™s own digital data. MultimediaÂ theft has driven the attention of many stakeholders who spend huge money and precious time in creating or making such valuable digital data. AmongÂ all the multimedia entities, image files are more vulnerable for theft since it is the basic component of any visuals. The notion of this research work isÂ to propose an image theft detection model which will determine whether partial theft or complete theft of an image has occurred or not. A biometricÂ feature, i.e., fingerprint of the owner is embedded on the digital image at a micro level, such that even a very small portion of image theft can beÂ determined, and the ownership of the image can be claimed by the owner. This research is limited to the spatial domain, i.e. raw image. AssessmentÂ metrics of the results shows that embedding the biometric feature on an image does not distort the image quality and its artifacts.

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Nithyanandam Pandian

Papers

Reversible data hiding methods in integer wavelet transform

JPEG Metadata: A complete study

A novel image theft identification using biometric feature

Iris Recognition Using Integer Wavelet Transform and Log Energy Entropy

Augmenting the detection of online image theft using diagonal transformation and iris biometric watermarking