Lossless Image Compression and Secure Storage of Medical Images

Abstract

This thesis presents a new methodology which performs both lossless compression and secure storage of binary and gray scale images. The compression is based on SCAN language and it is lossless in nature. The SCAN is a formal language based two dimensional spatial-accessing methodology which can efficiently specify and generate a wide range of scanning paths or space filling curves. Prior to the compression, a framework is presented which ensures the secure storage of images on basis of division of knowledge. Finally, QR code is used for efficient indexing of the secure images. QR codes are 2-dimensional bar codes which can store huge amount of data as compared to 1-dimensional barcodes. The results are analysed constrained to medical images in the hope of getting better results than that of the generic domain. Thus, this thesis presents compression specific SCAN language, compression-decompression algorithms, framework ensuring security and indexing, and test results of the methodology.