Trainable COSFIRE filters for vessel delineation with application to retinal images
We propose B-COSFIRE filters for the segmentation of blood vessels in retinal images. A B-COSFIRE filter combines the aligned responses of DoG filters with geometric mean. B-COSFIRE filters are trainable and achieve rotation-invariance efficiently. We evaluate the B-COSFIRE approach on DRIVE, STARE and CHASE-DB1 benchmark data sets. We achieve better effectiveness and efficiency than other unsupervised approaches.
cosfire delineation retinal image analysis trainable filters vessel segmentation