File Exchange

image thumbnail

Trainable COSFIRE filters for curvilinear structure delineation in images

version (13 MB) by Nicola Strisciuglio
B-COSFIRE filters detect line at different orientations by combining the responses of DoG filters.


Updated 28 Aug 2017

View License

We propose a filter that selectively responds to vessels and that we call B-COSFIRE with B standing for bar which is an abstraction for a vessel. It is based on the existing COSFIRE (Combination Of Shifted Filter Responses) approach.
A B-COSFIRE filter achieves orientation selectivity by computing the weighted geometric mean of the output of a pool of Difference-of-Gaussians filters, whose supports are aligned in a collinear manner. It achieves rotation invariance efficiently by simple shifting operations.
The proposed filter is versatile as its selectivity is determined from any given vessel-like prototype pattern in an automatic configuration process. We configure two B-COSFIRE filters, namely symmetric and asymmetric, that are selective for bars and bar-endings, respectively. We achieve vessel segmentation by summing up the responses of the two rotation-invariant B-COSFIRE filters followed by thresholding.
The B-COSFIRE filters can be used for detection of any elongated patterns in images:
- blood vessels in medical images
- roads and rivers in aerial images
- leaf nerves in natural images
- tiles in mosaics and textured images
The code is continuosly updated in the GitLab repository
If you use this script please cite the following papers:
[1] "George Azzopardi, Nicola Strisciuglio, Mario Vento, Nicolai Petkov, Trainable COSFIRE filters for vessel delineation with application to retinal images, Medical Image Analysis, Available online 3 September 2014, ISSN 1361-8415,"
[2] "N. Strisciuglio, G. Azzopardi, M. Vento, and N. Petkov" - Supervised vessel delineation in retinal fundus images with the automatic selection of B-cosfire filters. Machine Vision and Applications, doi:10.1007/s00138-016-0781-7
V1.4: Added CrackDetectionCluster.m - Experimental code (and data) to replicate results in the CAIP17 paper.
V1.3: Examples added, which are in the paper "N. Strisciuglio, N.Petkov - Delineation of line patterns in images using B-COSFIRE filters, IWOBI 2017". Correction of the approximated computation of the shifting vectors.
V1.2: Visualize B-COSFIRE output response and segmented image when Application() is called without output parameters.
V1.1: Computation of the orientation map added.

Cite As

Nicola Strisciuglio (2021). Trainable COSFIRE filters for curvilinear structure delineation in images (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2012a
Compatible with any release
Platform Compatibility
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!