Algorithm for fuzzy based compression of gray JPEG images for big data storage

Abstract

In the current era of big data and data mining, efficient storage of images is very important. In the collected datasets from blogs or social network sites, images are one of the prominent part of that datasets. Images took very large space for storage and even loading when required by the third party. So, image compression is one of the important part in big data and effective data mining. These applications require rapid image processing both at the front and back end. So, one of the most important step in storing and retrieving images is the effective compression of images. Images should be stored in compressed form and compression should not decrease the quality of the image. Many standards for compression of grey images are available. However, this area is still open for research purpose. Moreover, increase in variety of images over the internet demand the use of fuzzy based compression techniques, as also mentioned. In this paper, fuzzy based technique is used for compressing the grey JPEG images. It provides high level of compression and reduced level of errors in the images. Proposed technique also reduced different type of artifacts such as blocking artifacts, ringing artifacts and false contouring. Proposed compression can be effectively used for big data based storing and retrieval of images.