LOSSY IMAGE COMPRESSION USING FREEMAN CHAIN CODE REPRESENTATION

Abstract

In this study, we suggested an algorithm that made use of a Freeman chain code-based compression technique. The method consists of two segments such as compression and decompression. The first is a compression algorithm that begins by obtaining the chain code for a specific colour value and then saving the location of the start point for the chain code, colour value, level of the image, and chain code in a compressed text file. The next step is to remove all colour values associated with the chain code from the input image and shrink the input image. The algorithm repeats the previous steps until there are no colour values with significant chain code. The second step is to create the original image using the chain code, start point, colour value, and level of the image. The second part is to reconstruct the original image by using the start point, colour value, and chain code. We discover that this method is appropriate for the representation of lossy images based on the findings of our experiments. In comparison to the Joint Bilevel Image Experts Group (JBIG) compressor, the results are more effective at compressing data