Evaluation of image descriptors for urban-rural classification of aerial images

Daniel Cortés, Mariko Nakano, Hisashi Koga, Hector Perez

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

In this paper, fourteen descriptors are evaluated for urban-rural classification of aerial images. Among these fourteen descriptors, eleven descriptors consist of texture-based, color-based con combination of these two descriptors. Rest three descriptors are based on dictionaries generated using the Lempel-Ziv-Welch (LZW) data compression algorithm. The classification is carried out using Support Vector Machine (SVM) with radial basis function as kernel function and KNN algorithm. The performance of these images descriptors are evaluated using accuracy, precision, sensitivity and specificity. From evaluation results, we conclude the Gabor descriptor combined with Dominant Color descriptor provides better performance, obtaining its accuracy more than 91%.

Idioma originalInglés
Título de la publicación alojadaNew Trends in Intelligent Software Methodologies, Tools and Techniques - Proceedings of the 16th International Conference, SoMeT 2017
EditoresHamido Fujita, Ali Selamat, Sigeru Omatu
EditorialIOS Press BV
Páginas204-213
Número de páginas10
ISBN (versión digital)9781614997993
DOI
EstadoPublicada - 2017
Evento16th International Conference on New Trends in Intelligent Software Methodology Tools, and Techniques, SoMeT 2017 - Kitakyushu, Japón
Duración: 26 sep. 201728 sep. 2017

Serie de la publicación

NombreFrontiers in Artificial Intelligence and Applications
Volumen297
ISSN (versión impresa)0922-6389
ISSN (versión digital)1879-8314

Conferencia

Conferencia16th International Conference on New Trends in Intelligent Software Methodology Tools, and Techniques, SoMeT 2017
País/TerritorioJapón
CiudadKitakyushu
Período26/09/1728/09/17

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