Abstract
Technological advances have evolved in all the directions including the biomedical, because of which a record number of lives are saved every day. The advancement has now surpassed the tools level, now the doctors with the help of new tools can also detect diseases, which saves the response time. In this paper, we will work on one such technique which will help in retrieving the similar type of images with the help of their features. In this paper, the features such as Texture features, LBP features, Retrieval feature, which are processed with hash coding and relevance feedback to get the final results. The framework provides the output utilizing a hash coding classifiers which predict the image from the database of the images. The images are classified on a global level with the help of multiple low-level features.
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 callMore From: International Journal of Scientific Research in Computer Science, Engineering and Information Technology
Disclaimer: 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.
