A comparative analysis of SIFT, SURF and ORB on sketch and paint based images Online publication date: Thu, 11-Nov-2021
by R. Radha; M. Pushpa
International Journal of Forensic Engineering (IJFE), Vol. 5, No. 2, 2021
Abstract: Image retrieval has been one of the most interesting and emergent research areas in the field of computer vision. Content-based image retrieval (CBIR) systems are used in order to automatically index, search, retrieve and browse images from the databases. Content-based image retrieval system consider colour and texture features of the image, however those features are different in transformed images even though it is the toughest challenge for the CBIR to understand the image. Human perspective that has been based on input is essential for any retrieval system. Hand drawing images and painting images are considered as query image for this retrieval system. This paper has explored few eminent feature extraction techniques like scale invariant feature transform (SIFT), speeded up robust features (SURF) and oriented FAST and rotated BRIEF (ORB) as well as the performances of these techniques for sketch and paint based images. The suitable extraction technique is identified by this examination, the significance of SIFT, SURF and ORB features are listed.
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