  Any Universal Steganalysis algorithm developed should be tested with various
stego-images to prove its efficiency. This work is aimed to build the
stego-image database which is obtained by implementing various RGB Least
Significant Bit Steganographic algorithms. Though there are many stego-images
sources available on the internet it lacks in the information such as how many
rows has been infected by the steganography algorithms, how many bits have been
modified and which channel has been affected. These parameters are important
for Steganalysis algorithms and it helps to rate its efficiency. Images are
chosen from board categories such as animals, nature, person to produce variety
of Stego-Image.
