Adjusting image stego practicality via YCbCr color space formation

Information technology has revolutionized the field of communication in the digital age. However, these advancements have also raised significant security concerns. Protecting classified information is critical, and steganography is widely used to ensure confidentiality by embedding secret messages into media files in a way that makes them nearly undetectable. Among the various steganographic techniques, the Least Significant Bit (LSB) method is a commonly used approach. However, determining the optimal color space that balances image quality and data hiding capacity remains an active area of research. This study aims to bridge this gap by proposing a generalized evaluation framework that systematically analyzes ten color spaces RGB, HSV, HSI, YUV, YIQ, YCbCr, XYZ, LAB, LMS, and xyY using the LSB method. The framework involves applying LSB embedding across all color spaces, evaluating security using eight standard metrics (MSE, PSNR, SSIM, NAE, NCC, AD, MD, SC). The study further presented a normalized performance score for each space. Experimental results showed that YCbCr consistently outperforms others, achieving highest generalized score ranging between 0.875 and 0.890 for different testing images. The proposed framework provided attractive reproducible and scalable foundation for color space analysis within image steganography.