Name
Abstract | ||
|---|---|---|
Edge detection is a basic technique used as a preliminary step for, e.g., object extraction and recognition in image processing. Many of the methods for edge detection can be fit in the breakdown structure by Bezdek, in which one of the key parts is feature extraction. This work presents a method to extract edge features from a grayscale image using the so-called ordered directionally monotone functions. For this purpose we introduce some concepts about directional monotonicity and present two construction methods for feature extraction operators. The proposed technique is competitive with the existing methods in the literature. Furthermore, if we combine the features obtained by different methods using penalty functions, the results are equal or better results than state-of-the-art methods. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-91473-2_23 | Communications in Computer and Information Science |
Keywords | Field | DocType |
Edge detection,Feature extraction,Ordered directionally monotone functions,Penalty functions | Monotonic function,Pattern recognition,Computer science,Edge detection,Image processing,Feature extraction,Operator (computer programming),Artificial intelligence,Grayscale,Monotone polygon | Conference |
Volume | ISSN | Citations |
853 | 1865-0929 | 0 |
PageRank | References | Authors |
0.34 | 13 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cédric Marco-Detchart | 1 | 15 | 5.80 |
| Carlos Lopez-Molina | 2 | 231 | 21.58 |
| Javier Fernandez | 3 | 782 | 46.37 |
| Miguel Pagola | 4 | 979 | 45.68 |
| Humberto Bustince | 5 | 1938 | 134.10 |