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.
Bhattacharya et al. (Fri,) studied this question.