Linear feature enhancement based on morphological operation and Gabor function

Authors:
Ran Su;Changming Sun;Chao Zhang;Tuan D. Pham
Affiliations:
The University of New South Wales, Canberra, ACT, Australia;CSIRO Mathematics, Informatics and Statistics, NSW, Australia;The University of New South Wales, Canberra, ACT, Australia;The University of Aizu, Fukushima, Japan
Venue:
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
Year:
2012

Citing 9
Cited 0

Unsupervised texture segmentation using Gabor filters

Pattern Recognition
Fingerprint Image Enhancement: Algorithm and Performance Evaluation

IEEE Transactions on Pattern Analysis and Machine Intelligence
3D Multi-scale line filter for segmentation and visualization of curvilinear structures in medical images

CVRMed-MRCAS '97 Proceedings of the First Joint Conference on Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery
Shape Preserving Filament Enhancement Filtering

MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Muliscale Vessel Enhancement Filtering

MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Multi-scale line segmentation with automatic estimation of width, contrast and tangential direction in 2D and 3D medical images

CVRMed-MRCAS '97 Proceedings of the First Joint Conference on Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery
Handwriting Recognition

Handwriting Recognition
Vessel enhancement filter using directional filter bank

Computer Vision and Image Understanding
Junction detection for linear structures based on Hessian, correlation and shape information

Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

In many image processing tasks, feature enhancement is an important preprocessing step. It is the process of adjusting images so that the results are more suitable for analysis. Good enhancement results of linear features such as vessels or neurites can be inputs for segmentation or tracking. In this paper, we propose a novel linear feature enhancement method based on morphological operation and Gabor function, which can enhance and smooth linear features. We use and improve the Hessian matrix to calculate the orientation information for our directional morphological operation and Gabor smoothing. An approach for junction enhancement in each branch is also proposed here. We present the results of our algorithm on images of different types. The obtained outputs show that the proposed approach can achieve very good results.