Name
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. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2425836.2425857 | IVCNZ |
Keywords | Field | DocType |
directional morphological operation,junction enhancement,smooth linear feature,gabor smoothing,novel linear feature enhancement,linear feature,feature enhancement,good enhancement result,good result,gabor function,hessian,junction | Computer vision,Pattern recognition,Segmentation,Computer science,Image processing,Hessian matrix,Preprocessor,Smoothing,Artificial intelligence | Conference |
Citations | PageRank | References |
1 | 0.36 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ran Su | 1 | 28 | 3.36 |
| Changming Sun | 2 | 895 | 88.21 |
| Chao Zhang | 3 | 8 | 2.73 |
| Tuan Pham | 4 | 503 | 73.75 |