Abstract
A Content Based Image Retrieval is proposed using two techniques in order to show a comparative analysis. The comparative analysis points out it’s overall performance depends on the type of techniques used to extract multiple features and similarity metrics between the query image and images database. The first method uses colour histogram to extract colour features and the second method uses the Fast Discrete Curvelet Transform (FDCT) for the same process. In the first method, based on the colour features the query and database images were compared by using chi-square distance. Colour-histograms for both images were obtained and the images with most similarities are displayed (five images in this case). In the second method, instead of one feature (colour in the first case), a set of features are taken into consideration for calculating the feature vector. Once computation of feature vector is done, database and query images are compared to find out the top five similar images and results are displayed to the user.
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Sugamya, K., Pabboju, S., Vinaya Babu, A. (2017). A Comparative Analysis for CBIR Using Fast Discrete Curvelet Transform. In: Saini, H., Sayal, R., Rawat, S. (eds) Innovations in Computer Science and Engineering. Lecture Notes in Networks and Systems, vol 8. Springer, Singapore. https://doi.org/10.1007/978-981-10-3818-1_3
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DOI: https://doi.org/10.1007/978-981-10-3818-1_3
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