Background: The analysis of retinal images can help to detect retinal abnormalities that
are caused by cardiovascular and retinal disorders.
Objective: In this paper, we propose methods based on texture features for mining and analyzing
information from retinal images.
Methods: The recognition of the retinal mask region is a prerequisite for retinal image processing.
However, there is no way to automatically recognize the retinal region. By quantifying and
analyzing texture features, a method is proposed to automatically identify the retinal region. The
boundary of the circular retinal region is detected based on the image texture contrast feature,
followed by the filling of the closed circular area, and then the detected circular retinal mask region
can be obtained.
Results: The experimental results show that the method based on the image contrast feature can be
used to detect the retinal region automatically. The average accuracy of retinal mask region detection
of images from the Digital Retinal Images for Vessel Extraction (DRIVE) database was 99.34%.
Conclusion: This is the first time these texture features of retinal images are analyzed, and texture
features are used to recognize the circular retinal region automatically.