Abstract
This paper proposes a decision support system to recognizing retinal diseases. This paper uses a smartphone platform and cloud computing as the base of the system. A microscopic lens is attached int` the smartphone camera to capture the user retinal image for recognizing the user`s retinal condition. An application is assembled in computer and then installed in to the smartphone. The application role is to connect between the system in smartphone and system in cloud, the application will send the retinal image to the cloud system to be classified. The paper uses OCFE (optimized classifier based on feature elimination) algorithm as the classifier. The retinal image is trained using combination of two ophthalmology databases DIARETDB1 v2.1 and STARE. Therefore, this system average accuracy is 88%, while the average error rate is 12%.
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: The Journal of Korea Institute of Information, Electronics, and Communication 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.
