Name
Abstract | ||
|---|---|---|
The objectives of this paper is to present a novel adaptive edge extraction algorithm, based on processing 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 detectability. 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. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ICASSP.2006.1660453 | 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, Vols 1-13 |
Keywords | Field | DocType |
algorithm design and analysis,image resolution,gaussian processes,adaptive filters,computer vision,histograms,quantization,detectors,edge detection | Canny edge detector,Histogram,Computer science,Edge detection,Gaussian process,Artificial intelligence,Gaussian filter,Computer vision,Mathematical optimization,Deriche edge detector,Pattern recognition,Gaussian blur,Image resolution | Conference |
ISSN | Citations | PageRank |
1520-6149 | 1 | 0.37 |
References | Authors | |
2 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Magid Khallil | 1 | 1 | 0.37 |
| Amar Aggoun | 2 | 115 | 21.34 |