Comparative analysis on the image steganographic algorithms

Abstract

As a result of recent technological advancements in digitalization, a vast amount of data is generated every day. With the increased usage of the Internet, it is becoming increasingly difficult to prevent black hat hackers from disclosing critical and secret information. As a result, this research contributes to identifying the best and most efficient algorithm from among the three opted image steganographic algorithms, which are Pixel Value Differencing (PVD), Optimum Pixel Value Adjustment Procedure (OPAP), and Discrete Cosine Transform (DCT), as well as the image format pairing that can facilitate the most data capacity while maintaining the highest image quality, resilience, and undetectability. The purpose of this research is to apply the three image steganographic algorithms to coloured and grayscale images in the PNG, JPG, and BMP formats. The research technique for the intended study activity is divided into three parts. Each step is intended to accomplish a certain goal. Peak Signal-to-Noise Ratio (PSNR) and Mean Square Error (MSE) were the two performance metrics utilized to evaluate the algorithms. For the experiment, seven (7) separate standard pictures of 512 x 512 pixels and 1024 x 1024 pixels in colour and grayscale are obtained and employed. The three algorithms were analysed, assessed, and compared at the end of this study in terms of robustness, capacity, and imperceptibility. In a nutshell, OPAP is the best and most efficient algorithm which can be used to conceal the secret text without affecting the image quality while OPAP works best with grayscale images of 1024 x 1024 px to produce an excellent output in terms of high robustness, imperceptibility, and capacity.