Name
Abstract | ||
|---|---|---|
The problem we address in this paper is the segmentation and hierarchical grouping in digital images. In terms of image acquisition protocol, no constraints are posed to the user. At first, a histogram thresholding provides numerous segments where a homogeneity criterion is respected. Segments are merged together using similarity properties and aggregated in a hierarchy based on spatial inclusions. Shape and color features are extracted on the produced segments. Tests performed on Oxford Flower 17 [8] show that our method outperforms a similar one and allow the relevant object selection from the hierarchy. In our case, this approach represents the first stage towards flower variety identification. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-40261-6_47 | COMPUTER ANALYSIS OF IMAGES AND PATTERNS, PT I |
Keywords | Field | DocType |
segmentation, hierarchical grouping, plant recognition | Acquisition Protocol,Computer vision,Histogram,Pathos,Homogeneity (statistics),Pattern recognition,Segmentation,Computer science,Digital image,Artificial intelligence,Thresholding,Hierarchy | Conference |
Volume | ISSN | Citations |
8047 | 0302-9743 | 1 |
PageRank | References | Authors |
0.39 | 12 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Loreta Adriana Suta | 1 | 2 | 1.10 |
| Scuturici Mihaela | 2 | 37 | 6.91 |
| Vasile-Marian Scuturici | 3 | 119 | 20.95 |
| Serge Miguet | 4 | 255 | 36.41 |