Abstract
This chapter first discusses oRGB-SIFT descriptor, and then integrates it with other color SIFT features to produce the Color SIFT Fusion (CSF), the Color Grayscale SIFT Fusion (CGSF), and the CGSF+PHOG descriptors for image classification with special applications to image search and video retrieval. Classification is implemented using the EFM-NN classifier, which combines the Enhanced Fisher Model (EFM) and the Nearest Neighbor (NN) decision rule. The effectiveness of the proposed descriptors and classification method is evaluated using two large scale and challenging datasets: the Caltech 256 database and the UPOL Iris database. The experimental results show that (i) the proposed oRGB-SIFT descriptor improves recognition performance upon other color SIFT descriptors; and (ii) the CSF, the CGSF, and the CGSF+PHOG descriptors perform better than the other color SIFT descriptors.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
