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EnglishAccurately and automatically detecting image orientation is a task of great importance in intelligent image processing. In this paper, we present automatic image orientation detection algorithms based on these features: color moments; harris corner; phase symmetry; edge direction histogram. The statistical learning support vector machines, AdaBoost, Subspace classifier are used in our approach as classifiers. We use Borda Count as combination rule for these classifiers. Large amounts of experiments have been conducted, on a database of more than 6,000 images of real photos, to validate our approaches. Discussions and future directions for this work are also addressed at the end of the paper.
| Titolo: | Detector Of Image Orientation Based On Borda-count |
| Autore/i: | NANNI, LORIS; LUMINI, ALESSANDRA |
| Autore/i Unibo: | |
| Anno: | 2005 |
| Titolo del libro: | Pattern Recognition and Image Analysis Second Iberian Conference, IbPRIA 2005, Estoril, Portugal, June 7-9, 2005, Proceeding, Part II |
| Pagina iniziale: | 231 |
| Pagina finale: | 238 |
| Abstract: | Accurately and automatically detecting image orientation is a task of great importance in intelligent image processing. In this paper, we present automatic image orientation detection algorithms based on these features: color moments; harris corner; phase symmetry; edge direction histogram. The statistical learning support vector machines, AdaBoost, Subspace classifier are used in our approach as classifiers. We use Borda Count as combination rule for these classifiers. Large amounts of experiments have been conducted, on a database of more than 6,000 images of real photos, to validate our approaches. Discussions and future directions for this work are also addressed at the end of the paper. |
| Data prodotto definitivo in UGOV: | 28-set-2005 |
| Appare nelle tipologie: | 4.01 Contributo in Atti di convegno |
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http://hdl.handle.net/11585/6797
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