| Revista: | Computación y sistemas |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000349841 |
| ISSN: | 1405-5546 |
| Autores: | González García, A. C1 Sossa Azuela, J. H2 Felipe Riverón, E. M2 Pogrebnyak, O2 |
| Instituciones: | 1Instituto Tecnológico de Toluca, Departamento de Ingeniería Eléctrica y Electrónica, Metepec, Estado de México. México 2Instituto Politécnico Nacional, México, Distrito Federal. México |
| Año: | 2007 |
| Periodo: | Oct-Dic |
| Volumen: | 11 |
| Número: | 2 |
| Paginación: | 143-156 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Aplicado, descriptivo |
| Resumen en español | The problem of retrieving images from a database is considered. In particular, we retrieve images belonging to one of the following six categories: 1) commercial planes in land, 2) commercial planes in air, 3) war planes in land, 4) war planes in air, 5) small aircraft in land, and 6) small aircraft in the air. During training, a wavelet–based description of each image is first calculated using Daubechies 4–wavelet transformation. The resulting coefficients are used to train a neural network (NN). During classification, test images are treated by the already trained NN. Three different ways to obtain the coefficients of the Daubechies transform were proposed and tested: from the entire image color channels, from the histogram of the biggest circular window inside the image color channels, and from the histograms of the square sub–images in the image color channels of the original image. 120 images were used for training and 240 for testing. The best efficiency of 88% was obtained with the third method |
| Resumen en inglés | The problem of retrieving images from a database is considered. In particular, we retrieve images belonging to one of the following six categories: 1) commercial planes in land, 2) commercial planes in air, 3) war planes in land, 4) war planes in air, 5) small aircraft in land, and 6) small aircraft in the air. During training, a wavelet–based description of each image is first calculated using Daubechies 4–wavelet transformation. The resulting coefficients are used to train a neural network (NN). During classification, test images are treated by the already trained NN. Three different ways to obtain the coefficients of the Daubechies transform were proposed and tested: from the entire image color channels, from the histogram of the biggest circular window inside the image color channels, and from the histograms of the square sub–images in the image color channels of the original image. 120 images were used for training and 240 for testing. The best efficiency of 88% was obtained with the third method |
| Disciplinas: | Ciencias de la computación |
| Palabras clave: | Computación, Recuperación de imágenes, Transformada Wavelet, Clasificación de imágenes |
| Keyword: | Computer science, Computing, Image retrieval, Wavelet transform, Images classification |
| Texto completo: | Texto completo (Ver HTML) |
