Image processing techniques are essential part of the current computer technologies and that it plays vital role in various applications like medical field, object detection, video surveillance system, computer vision etc. The important process of Image processing is Image Segmentation. Image Segmentation is the process of splitting the images into various tiny parts called segments. Image processing makes to simplify the image representation in order to analyze the images. So many algorithms are developed for segmenting images, based on the certain feature of the pixel. In this paper different algorithms of segmentation can be reviewed, analyzed and finally list out the comparison for all the algorithms. This comparison study is useful for increasing accuracy and performance of segmentation methods in various image processing domains.
Data is expanding beyond the speed of light and hence a lighting speed devices and networks are required for a better and more reliable system for data storage. Cloud computing is a boon for larger, remote data storage at a virtual location. Cloud computing encounters major challenges
such as security, connectivity and backup recovery. In this paper, a novel methodology is proposed and concentrated on backup and recovery management to provide a fault tolerance and recognition cloud system with a higher order of reliability and scalability. The methodology proposes an approach
of data segmentation and token generation for data split-up using tailing terminology of appending cloud storage location or addresses. Thus the faulty cloud server missing a location segment is recognized within a smaller broadcasting limit and fetches backup from secure neighboring sources.
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