• KR Anirudh Yadav
• Ravishankar
• Abdulla Nishal
• Aravind Nayak
• Shreya Shetty, Suresha D

Image steganography concerns itself with the hiding of secret message information within digital images; hence, it is a covert communication technique. Cryptography scrambles the plaintext into an unreadable format, while steganography goes one step farther, hiding the plaintext's very existence. The interest of the project involves using the Least Significant Bit method in embedding hidden messages within images; pixel values are changed only at the very least possible, such that no conspicuous difference appears in the overall view of the image. The report highlights various theoretical aspects of image steganography, describes the methodology adopted in the implementation, and discusses security factors that must be taken into account. The report stresses the merits of the LSB approach in terms of simplicity, high capacity, and less degradation to visual quality of the image. The encoding and decoding of hidden messages have been implemented in Python using OpenCV and several other supporting libraries. A range of tests was conducted to evaluate the performance of the system regarding data capacity, security, and integrity of the image. The results confirm that LSB-based image steganography can effectively secure information that is sensitive to the maximum degree while maintaining almost the same appearance of the carrier image.

IMAGE STEGANOGRAPHY USING MACHINE LEARNING

"IMAGE STEGANOGRAPHY USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.19-27, July-2025, Available :http://www.jetir.org/papers/JETIRGX06005.pdf

"IMAGE STEGANOGRAPHY USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. pp19-27, July-2025, Available at : http://www.jetir.org/papers/JETIRGX06005.pdf