Retinal-Image-Quality-Assessment
Analyse adequacy of a retinal image
Source
feature.cpp
Reads in an image of the retina and calculates the feature vector values
result.cpp
Takes in the feature vector and the coefficient vector(theta calculated using logistic regression) and declares whether the image is gradable or not
Dependencies
- OpenCV 3.0.0
Trial
Run:
$ make all
$./AssessImage.sh /path/to/retinal_image
Sample Run
$ make all
$ ./AssessImage.sh Images/1.jpg
Output:
Ungradable Retinal Image
Gradable Retinal Image
References
- Herbert Davis, Stephen Russell, Eduardo Barriga, Michael Abramoff and Peter Soliz - "Vision-based, Real-time Retinal Image Quality Assessment"
- Gopal Datt Joshi, Jayanthi Sivaswamy - "Colour Retinal Image Enhancement based on Domain Knowledge"
- A. Gebejes, R. Huertas - "Texture Characterization based on Grey-Level Co-occurrence Matrix"
- João Miguel Pires Dias, Carlos Manta Oliveira, Luís A. da Silva Cruz - "Retinal image quality assessment using generic image quality indicators"