On data compression methods

It is very important to compress and size the images because they are stored in very large quantities of binary images that have a wide range of applications in fields such as text, fingerprint, and map. With increased ever increasing of binary images in a wide range of applications like text, fingerprint, and mapping, its storage and accumulation in huge amounts makes it important to compress and reduce size of the images. In this thesis, data compression hechniques are investigated. By introducing a new coding system, a technique has been proposed that can commpress binary images more efficiently. It has been shown that the new coding system devoloped can provide high compression especially for systems with consecutive repetitions. Anohter advantage of this compression method is its iterative applicability on compressed versions of the same data several times. In this work, a new coding method for lossless compression of binary images is proposed. The most commonly known run-length encoding method in this area is compared with the newly developed method. The comparative results obtained show that the new method is successful in compressing binary images. Especially in images with long consecutive identical bits, the effectiveness of the new method has been shown to be better than the run-length method. The new coding system proposed in this study can also be used for encryption.