Abstract
Providing biometric data through multimedia has made it difficult to ensure secure communication and authentication in the digital age. This research showcases an advanced dual-biometric steganographic system that incorporates signature and fingerprint characteristics in a single cover image using Discrete Wavelet Transform (DWT) and Disputed Cosine Transform (DCT). An Adaptive Bit Placement (ABP) approach is proposed, which intelligently selects embedding positions by considering coefficient significance and biometric importance to balance imperceptibility, robustness, and embedding.To verify its efficacy, the system was compared to standard benchmark images and provided with live biometric data samples. The experimental outcomes demonstrate that the proposed ABP-based Dual Biometric Steganography (ABPDBS) is significantly superior to current methods. While the current methods show Peak Signal to Noise Ratio (PSNR) values between 34 and 39 dB and Structural Similarity Index Measurement (SSIM) scores between 0.90 and 0.96, and embedding capacities below 0.30 bpp, the proposed approach yields average PSNR improvements of 22–36% (47.31-50.76dB), mean value of SSIM improvements of 2–11% (0.9748 with maximum reach to 0.9995) and an embedding capacity increases of 16% (0.33 bpp). Proposed method also provides overall better integration performance in these new techniques than those previously described. These results imply that the system is highly imperceptible; resilient to typical signal processing attacks, and has greater payload strength. In general, this research presents a secure and efficient framework for dual-biometric embedding which can enhance multimodal authentication systems suitable for high-security scenarios.
Data availability
The dataset supporting the findings of our research has been deposited in a publicly accessible GitHub repository. The direct link is provided below: GitHub Repository Link: [https://github.com/AbhrenduBhattacharya/Adaptive-bit-placement-for-Dual-Biometry](https:/github.com/AbhrenduBhattacharya/Adaptive-bit-placement-for-Dual-Biometry).
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Acknowledgements
The data sets used from sipi data sets available under miscellaneous section of https://sipi.usc.edu/database/database.php?volume=misc%26image=10#top. USC –SIPI Image Database Volume 3. This article does not contain any studies involving human participants, animals, or sensitive personal data performed by any of the authors. Therefore, ethical approval and informed consent were not required for this research.
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Author 1 Contribution: Dr. Abhrendu Bhattacharya was the leader of the conceptualization and design of the proposed adaptive bit placement algorithm and its applications to dual biometric steganography. The embedding and extraction under the hybrid DWT-DCT transform domain was thus a key focus area of Dr. Bhattacharya. He supervised the experimental setup, guided the performance evaluation through PSNR, SSIM, and capacity metrics, and co-supervised the integration of biometric modalities (signature and fingerprint) within the steganographic flow. Dr. Bhattacharya was also responsible for drafting the manuscript, interpreting the results, and ensuring the research met the standards of scientific integrity and originality.Author 2 Contribution: Dr. Amit R. Welekar gave expert guidance on the theoretical framework and mathematical modeling aspects of the hybrid DWT-DCT transform implemented in the steganographic procedure. He backed the validation of the algorithm against various test cases and helped in fine-tuning the strategy for adaptive embedding to ensure higher fidelity and robustness. Dr. Welekar also delved into the related study literature to provide an exhaustive background for the study and assisted with proofreading of the final manuscript so as to elevate clarity, structure, and academic tone.Author 3 Contribution: Dr. Paramita Sarkar made significant contributions during the biometric data acquisition and preprocessing stages. She focused on fine-tuning the extraction of fingerprint and signature features for steganographic embedding. Additionally, she was instrumental in implementing the algorithm using Python and contributed to the visual analysis, which included comparing histograms and evaluating stego-cover images. Dr. Sarkar also took a leading role in compiling the experimental results, creating graphs and radar plots, and aiding in the interpretation of performance metrics to draw meaningful insights.Author 4 Contribution: Dr. Rajesh Bose was involved in algorithm optimization, including proper fine-tuning of the adaptive bit placement for the sake of robustness and imperceptibility. He contributed valuable insights into the processing of biometric data and the selection of preprocessing techniques to improve the embedding fidelity. Dr. Bose contributed to data analysis, performance comparison vis-à-vis old methodologies, and enhancement of the visual assessment process through, for example, histograms and radar charts. He also reviewed and edited the manuscript to test for technical accuracy, consistency, and alignment with publication standards.Author 5 Contribution: Dr. Sandip Roy contributed to the technical design, refinement, and validation of the Adaptive Bit Placement framework for dual-biometric steganography. He assisted in methodological optimization and supported result interpretation to strengthen system performance evaluation. His inputs significantly enhanced the robustness and scientific accuracy of the proposed model.Author 6 Contribution: Achyut Mitra played a key role in bringing the adaptive bit placement algorithm to life through the hybrid DWT-DCT technique. He took the lead in developing and testing Python-based steganography modules that allowed for the embedding and extraction of dual biometric data. Beyond that, Achyut was instrumental in data collection, overseeing experimental runs, and creating insightful visualizations like radar charts and histograms. He also lent a hand in compiling references and formatting the manuscript for submission, ensuring everything was polished and ready to go.
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Bhattacharya, A., Welekar, A.R., Sarkar, P. et al. Adaptive bit placement for dual biometric using signature and finger print for DWT-DCT picture steganography. Sci Rep (2026). https://doi.org/10.1038/s41598-026-37827-x
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DOI: https://doi.org/10.1038/s41598-026-37827-x
