Analysis of CBIR on the basis of Accuracy, BER and Entropy

Volume: 3    Issue: 5

Year of Publication: 2016

Pages: (1-8)

Authors: Sukhmanjeet Kaur, Gagandeep Singh

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Abstract

In this paper, we present associate economical algorithmic rule primarily based on SURF (Speeded up sturdy Features), SVM and NN. The method applies the SURF formula within the detection and ouline for image features; first it applies the SURF feature detector in extracting reference pictures and matching feature points within the image, respectively. In the process of feature points matching; the false matching points area unit eliminated through this formula. Finally, according to the remainder of point which may estimate the space geometric transformation parameters between two pictures and so matching method is completed. In this thesis, SURF algorithm is used to notice and descript the interest points; and match the interest points by using Surf [1, 3]. In this paper, the same is tried to retrieve with the employment of SURF and fed into Support Vector Machine (SVM) and NN (Neural Network) for further classification.The SURF technique is fast and sturdy interest points detector that is used in several laptop vision applications. For the implementation of this proposed work we have a tendency to use the Image Processing Toolbox under MATLAB Software.

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Keywords

Image processing, Matching, Surf, Neural Network and SVM.