Abstract
This paper proposes a trademark retrieval algorithm combining the image global features and local features. Firstly, extract pseudo Zernike moments of the retrieved image and sort them according to similarity. Candidate images are formed. Then, the SIFT features are used for matching the query image accurately with candidate images. Experimental results show that this method not only keeps high precision- recall of SIFT features and is superior than the method based on the single pseudo Zernike moments feature, but also improves effective retrieval speed compared to the single SIFT features. This method can be well applied to the trademark image retrieval system.
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.
