Design and Implementation of Image Authentication Technique using Probabilistic Principal Component Analysis

Digital watermarking play an important role in information security. It majorly focusses on the authentication of the information. The authentication provides the genuinity of the owner of the information. The present paper focuses on the development of a novel Probabilistic Principal Component Analysis based Transform domain wtaremerking method (PPCATDW). The proposed PPCATDW method uses wavelet transformation domain for watermarking process. It interanlly uses pricnipal component analysis based information for the identification of the influential representation points of the input image. The proposed method is experimented with the fourteen images and the results show the efficacy of the proposed method.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-31
DOI
https://doi.org/10.5281/zenodo.20470527
Primary Topic
Advanced Steganography and Watermarking Techniques
Type
article
Field-Weighted Citation Impact
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article

Design and Implementation of Image Authentication Technique using Probabilistic Principal Component Analysis

Khaja Mizbahuddin Quadry, Ayesha Parveen
Zenodo (CERN European Organization for Nuclear Research)
Advanced Steganography and Watermarking Techniques
article

Design and Implementation of Image Authentication Technique using Probabilistic Principal Component Analysis

Khaja Mizbahuddin Quadry, Ayesha Parveen
article en

Abstract

Digital watermarking play an important role in information security. It majorly focusses on the authentication of the information. The authentication provides the genuinity of the owner of the information. The present paper focuses on the development of a novel Probabilistic Principal Component Analysis based Transform domain wtaremerking method (PPCATDW). The proposed PPCATDW method uses wavelet transformation domain for watermarking process. It interanlly uses pricnipal component analysis based information for the identification of the influential representation points of the input image. The proposed method is experimented with the fourteen images and the results show the efficacy of the proposed method.

Zenodo (CERN European Organization for Nuclear Research)
Indian Institute of Technology Hyderabad (IN)
Openalex Percentile: Top 4%
Advanced Steganography and Watermarking Techniques
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