2016
DOI: 10.1016/j.cose.2016.01.003
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Privacy preservation for soft biometrics based multimodal recognition system

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Cited by 12 publications
(7 citation statements)
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References 19 publications
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“…Extract using {K,W}Public(blind)watermarking-neither cover-data nor embedded watermarks are required for extraction-this are the most challenging problem. Extract using {K}.Figure 3 Types of Biometric Module.A biometric [17] [18] identifier is one that is related to intrinsic human characteristics. They fall roughly into two categories: physical identifiers and behavioral identifiers.…”
Section: Types Of Watermarking Schemementioning
confidence: 99%
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“…Extract using {K,W}Public(blind)watermarking-neither cover-data nor embedded watermarks are required for extraction-this are the most challenging problem. Extract using {K}.Figure 3 Types of Biometric Module.A biometric [17] [18] identifier is one that is related to intrinsic human characteristics. They fall roughly into two categories: physical identifiers and behavioral identifiers.…”
Section: Types Of Watermarking Schemementioning
confidence: 99%
“…As per the less percentage of variations in physical traits in the human body for the biometric digital images are fingerprint and retina [20] [22]. [18]. So we should go for image processing concepts that are implemented in java.…”
Section: Existing Workmentioning
confidence: 99%
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“…We ascertain the coordinating score between two pictures utilizing hamming separation. The DCT system is High precision with lessened blunder rates [6][7] [8]. The proposed Feature Extraction calculation can be utilized for a bigger database, for example, for Aadhar in light of the fact that it requires less investment for highlight extraction and has less many-sided quality with lessened scientific weight on the framework and enhances great picture precision.…”
Section: Fingerprint and Retina Using Dct And Image Based Steganograpmentioning
confidence: 99%
“…Outcomes specify that this flaw was able to overcome the discussed confronts, thus aiding the data sharing for information discovery in applications related to healthcare. Sadhya [18] have presented a security-preserving structure for biometric dependent models by exploiting the common concept of various privacies. Therefore the implemented architecture offers security for biometric users devoid of negotiating its whole performance.…”
Section: A State-of-the-art Of Contributionsmentioning
confidence: 99%