A Hybrid Techniques To Improve Productivity Of Sequential Pattern Discovery Using SPADE Algorithm For Clustering Digital Images

Abstract

Today, all the digital images which are converted into frames from the video are stored in the form transactional databases in the cloud environment. This proposed work mainly focused on SPADE, for the new discovery of Sequential pattern in the digital images, which are stored in the sequential database. The existing solution to this problem leads to the repeated database scan due to transactional databases and also the quality of the images are poor due to complex hash structures. Proposed SPADE algorithm which decomposes the quality of image frame into smaller sub image frame which can be independently solved in primary memory and also improve the quality of the images rather than the transactional database. This proposed will compare the CPU utilization based on the transactional databases compared with proposed SPADE algorithm which proved to be more effective and efficient.