# PERFORMANCE ANALYSIS OF LSB, MSB AND COMBINED LSB-MSB ALGORITHM INTERMS OF IMAGE QUALITY AND ENCODING TIME.

Need help with a related project topic or New topic? Send Us Your Topic

## PERFORMANCE ANALYSIS OF LSB, MSB AND COMBINED LSB-MSB ALGORITHM INTERMS OF IMAGE QUALITY AND ENCODING TIME.

Chapter 1: Background of the Study

This project’s background is built on the concepts of data compression and encoding. This type of data compression and encoding is commonly used in steganography, video editing, and other applications.

For this assignment, we will use steganography to test each of the three methods’ image quality and encoding time. These activities are carried out using specific algorithms to obtain the desired outcome.

The algorithms that will receive special attention are the LSB (Least Significant Bit), MSB (Most Significant Bit), and combined LSB-MSB algorithms.

The Least Significant Bit Algorithm is recognised for its “security through obscurity” feature, which involves hiding data under a cover image or audio in the least significant bit. In a binary system, the lowest bit is known as the LSB.

The LSB is commonly used to conceal text or images within a cover picture. It works on the assumption that the human eye cannot distinguish between two shades separated by a little.

The Most Significant Bit Algorithm is based on the Most Significant Bit, often known as the highest bit value in a series of binary values. This approach embeds a hidden message in an image’s most important bit.

The Combined LSB-MSB algorithm is a blend of the aforementioned techniques. Some call it New Hybrid (a combination of the LSB and HSB algorithms). Wai et al. (2018).

It works by combining the LSB and MSB approaches to create a hybrid algorithm that embeds the secret message bits in both the least significant and most significant bits of the cover image.

1.2 Statement of the Problem

Finding the most efficient algorithms to encode and compress data formats has been an issue for as long as the electronic era. However, certain algorithms have restrictions that affect image quality and encoding time. This study intends to assess optimally, using a range of analytic methods, on data types such as photographs.

1.3 Motivation for the Study

This study was prompted by the fact that there are numerous methods for hiding and encoding information/text in steganography. We want to determine which algorithm(s) can be employed in specific instances.

1.4 Aims and Objectives of the Study

The goal of the performance analysis of the LSB, MSB, and combined LSB-MSB algorithms is to:

Examine the performance of the aforementioned algorithms for picture and image generation and compression.

Discover the best algorithms for compression and encoding.

Every algorithm and model should be constantly improved.

Combining the MSB and LSB approaches yields a hybrid algorithm that embeds secret message bits in the cover image’s least and most significant bits.

Compare the three approaches in terms of the encoding time.

Test the algorithms with various image formats and evaluate the image quality.

1.5 Outline of Methodology

This idea and project were implemented using the Java programming language. This was chosen due to its cross-platform nature and widespread use in steganography and cryptography of many picture formats.

1.6 SCOPE OF THE STUDY
The study examines the performance of three methods for encoding a variety of image formats such as.jpg,.gif, and.bmp. We also look at difficulties and how to address them. For this project, we would investigate on a smaller scale and test it before expanding the scope.

1.7 Significance of the Study
The work is particularly important in terms of researching, analysing, and proposing more efficient and reliable methods of encoding and compressing images. It also investigates the applications and potential improvements of LSB-based, MSB-based, and LSB-MSB-based steganographic algorithms.

Need help with a related project topic or New topic? Send Us Your Topic