Currency Value Detection and Counting using Feature Extraction and Classification Algorithms

Image processing is the area in which currently many predictions are performed from the captured images. Currency Value detection is aims at searching the features of the training dataset with the query image feature and obtains the respective value of the feature that has the match with query image. In present system the images are ompared and matched according to pixel values and few features extracted, which consumes a lot of time for execution instead we can extract the desirable features that are used to identify and classify the type of image. The proposed technique aims to reduce the searching time of image retrieval and hence it improves the performance of image retrieval system using best suitable feature extraction algorithms offered by Matlab and instead of sticking to one feature extraction algorithm it is better to apply multiple feature extraction methods that improves the accuracy. To build an effective classifier it is better to add new components and new changes to the existing algorithms that increase the good impact on the classifier.