| Journal: | Polibits |
| Database: | PERIÓDICA |
| System number: | 000383469 |
| ISSN: | 1870-9044 |
| Authors: | Dornaika, Fadi1 Moujahid, Abdelmalik1 Bosaghzadeh, Alireza1 El Merabet, Youssef2 Ruichek, Yassine3 |
| Institutions: | 1Universidad del País Vasco, Bilbao, Vizcaya. España 2Universite Ibn Tofail, Kenitra. Marruecos 3Universite de Technologiede Belfort-Montbeliard, Institut de Recherche sur les Transports, Belfort. Francia |
| Year: | 2015 |
| Season: | Ene-Jun |
| Number: | 51 |
| Pages: | 11-17 |
| Country: | México |
| Language: | Inglés |
| Document type: | Artículo |
| Approach: | Aplicado, descriptivo |
| English abstract | We present a framework for automatic and accurate multiple detection of objects of interest from images using hybrid image descriptors. The proposed framework combines a powerful segmentation algorithm with a hybrid descriptor. The hybrid descriptor is composed by color histograms and several Local Binary Patterns based descriptors. The proposed framework involves two main steps. The first one consists in segmenting the image into homogeneous regions. In the second step, in order to separate the objects of interest and the image background, the hybrid descriptor of each region is classiied using machine learning tools and a gallery of training descriptors. To show its performance, the method is applied to extract building roofs from orthophotos. We provide evaluation performances over 100 buildings. The proposed approach presents several advantages in terms of applicability, suitability and simplicity. We also show that the use of hybrid descriptors lead to an enhanced performance |
| Disciplines: | Ciencias de la computación |
| Keyword: | Procesamiento de datos, Detección de objetos, Descriptores, Imágenes, Edificios, Ortofotografía |
| Keyword: | Computer science, Data processing, Objects detection, Descriptors, Images, Buildings, Orthophotography |
| Full text: | Texto completo (Ver HTML) |
