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Research Article Open Access
A rate control framework for H.264/AVC based video coding is used to improve the gradient based features to increase Scale-Invariant Features Transform (SIFT) and Speeded up Robust Feature (SURF). In this, increased performance according to the Bag-of-features (BoFs) concept and also an improves Macro block (MB) categorization approach is carried out. First different QP values for each group is calculated and then the matching scores are collected as a function of the quantization parameters (QP) and an heuristic QP assignment approach for different groups used for I frames. Next part the rate control algorithm tests different numbers of features to be preserved, considers the human observer and conducts many experiments that shows the performance preserving the rate control framework. The proposed approach improves feature preservation and improvement in a real image retrieval system. It is fully standard compatible using the rate control framework.
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Author(s): Nandhini R , Raj Bharath S M
Signal Processing,Basic Electrical Engineering,Asynchronous Machines,Artificial Intelligence in Electronics,Analysis of Power Electronic Converters.