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linear indoctrination for numerous substantiation stratums using image fusion

C.PRETTY DIANA CYRIL,S.SARAVANAKUMAR

Published in International Journal of Advanced Research in Computer Science Engineering and Information Technology

ISSN: 2321-3337          Impact Factor:1.521         Volume:2         Issue:2         Year: 15 April,2014         Pages:375-384

International Journal of Advanced Research in Computer Science Engineering and Information Technology

Abstract

In this research paper where Image Processing is one of the emerging areas that are catching up, and NASA has predicted it to attain main stream adoption. The research process works on the global image processing adoption clearly shows that 51% of the firms are sceptical about Object tracking and close to 35% state that technology is still immature to track ground vehicle traffic. This research tries to address on clear object registration which is the process of alignment images and to determine both a stitched image and weighting mask functions of multiple input images for image blending. The target is then modelled by extracting spectral and spatial features for accurate multidimensional images. Here multiple objects can be tracked simultaneously with user initialized starting points. Establishing the transformation process in the input image has been adopted by Scale Invariant Feature Transforms. The Object tracking is done by Linear programming in continuous video frame for efficient search. Hence, an improved Object tracking detection has been developed by viola-Jones object detection framework by calculating Bhattacharya distance for spectral featuring.

Kewords

SIFT, Bhattacharya Algorithm, Kalman Filter.

Reference

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