Fast retrieval of images in secured content based image retrieval system
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Date
2017-07
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G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand)
Abstract
Content Based Image Retrieval is referred to a technique for retrieving images from database similar to query image. Retrieval is based on automated matching of features of query image with that of image database through some similarity evaluation. Due to the increment in advancement of technologies data has been increased to huge amount, hence securing these data is an important concern and to retrieve data from these large dataset in less amount of time is one of the challenging task for Content Based Image Retrieval System. Here we have implemented a method of image retrieval to overcome these challenges. Thus this research work focuses on analyzing the performance of CBIR based on GPU and using Daubechies Wavelet Transform and Arnold’s Cat Map. Analysis is performed in four phases, first phase compares different image feature descriptors. Second phase compares some members of Wavelet Family, then in third phase comparison of CBIR process using GPU CUDA and without using GPU CUDA is performed, final phase compares and analyze the performance of CBIR after applying GPU CUDA, Daubechies Wavelet-db35 for feature extraction and securing images using Arnold’s Cat Map algorithm. Results are evaluated based on the performance matrices i.e precision and recall and time consumed to retrieve images, encryption algorithm is tested on the basis on PSNR and MSE. This research work has been simulated in MATLAB.
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