Stegano Hiding with Improved Embedding Capacity Using LSB Techniques

Abstract

The increasing exchange of sensitive information through digital networks has intensified the need for effective and imperceptible information-hiding techniques. This study presents a Steganography Imaging System (SIS) designed to improve data embedding through the integration and automatic selection of multiple Least Significant Bit (LSB) techniques. The proposed system incorporates four embedding configurations, namely LSB1, LSB2, LSB3, and LSB4, to conceal textual information within digital images while preserving the visual characteristics of the cover image. The system performs both information embedding and retrieval and selects an appropriate LSB technique according to image and message requirements. The proposed approach was implemented in MATLAB and evaluated using a 120 × 120 image. Experimental results showed reported text-size values of 4,601 for LSB1, 4,861 for LSB2, 9,116 for LSB3, and 1,600 for LSB4. The findings demonstrate that embedding performance does not necessarily increase with a higher nominal LSB level, highlighting the importance of adaptive technique selection. Among the evaluated configurations, LSB3 achieved the highest reported embedding value, while LSB4 produced the lowest. The proposed SIS provides an integrated framework for comparing multiple LSB techniques and supports secure information hiding and retrieval while maintaining the perceptual quality of the resulting stego image. The study contributes to image steganography by emphasizing adaptive algorithm selection rather than reliance on a single fixed LSB configuration.

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