Name
Abstract | ||
|---|---|---|
The objectives of this paper is to present a novel edge extraction algorithm, based on differentiation of the local histograms of small non-overlapping blocks of the output of the first derivative of a narrow 2D Gaussian filter. It is shown that the proposed edge extraction algorithm provides the best trade off between noise rejection and accurate edge localisation and resolution. The proposed edge detection algorithm starts by convolving the image with a narrow 2D Gaussian smoothing filter to minimise the edge displacement, and increase the resolution and delectability. Processing of the local histogram of small non-overlapping blocks of the edge map is carried out to perform an additional noise rejection operation and automatically determine the local thresholds. The results obtained with the proposed edge detector are compared to the Canny edge detector. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1117/12.503023 | VISUAL COMMUNICATIONS AND IMAGE PROCESSING 2003, PTS 1-3 |
Keywords | Field | DocType |
edge detection, local histogram analysis, edge thresholding | Gaussian filter,Computer vision,Canny edge detector,Image gradient,Deriche edge detector,Computer science,Edge detection,Gaussian blur,Marr–Hildreth algorithm,Artificial intelligence,Signal edge | Conference |
Volume | ISSN | Citations |
5150 | 0277-786X | 0 |
PageRank | References | Authors |
0.34 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Abdelmagid Khalil | 1 | 0 | 0.34 |
| Amar Aggoun | 2 | 115 | 21.34 |
| Ahmed El-mabrouk | 3 | 0 | 0.34 |