Trainable COSFIRE filters for curvilinear structure delineation in images
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 https://gitlab.com/nicstrisc/B-COSFIRE-MATLAB
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, http://dx.doi.org/10.1016/j.media.2014.08.002"
[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
CHANGELOG
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.
Cita come
Nicola Strisciuglio (2024). Trainable COSFIRE filters for curvilinear structure delineation in images (https://www.mathworks.com/matlabcentral/fileexchange/49172-trainable-cosfire-filters-for-curvilinear-structure-delineation-in-images), MATLAB Central File Exchange. Recuperato .
Compatibilità della release di MATLAB
Compatibilità della piattaforma
Windows macOS LinuxCategorie
- Sciences > Biological and Health Sciences > Biomedical Imaging >
- Sciences > Neuroscience > Behavior and Psychophysics >
- Image Processing and Computer Vision > Image Processing Toolbox > Image Filtering and Enhancement > Image Arithmetic >
- Sciences > Biological and Health Sciences > Biomedical Imaging > Retinal Imaging >
Tag
Riconoscimenti
Ispirato da: Trainable COSFIRE filters for keypoint detection and pattern recognition
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Scopri Live Editor
Crea script con codice, output e testo formattato in un unico documento eseguibile.
B-COSFIRE/
B-COSFIRE/COSFIRE/
B-COSFIRE/Gabor/
B-COSFIRE/Performance/
B-COSFIRE/Preprocessing/
Versione | Pubblicato | Note della release | |
---|---|---|---|
1.4.0.0 | Added CrackDetectionCluster.m - Experimental code (and data) to replicate results in the CAIP17 paper. |
||
1.3.0.0 | 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.
|
||
1.2.0.0 | V1.2: Visualize B-COSFIRE output response and segmented image when Application() is called without output parameters. |
||
1.1.0.0 | Changelog
|
||
1.0.0.0 | this is not a toolbox |