Increasing Illumination Invariance of SURF Feature Detector through Color Constancy

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2013

Autores

petry, mr (Autor) Outra; António Paulo Moreira (Autor) FEUP; reis, lp (Autor) FEUP

Ata de Conferência Internacional

Título: PROGRESS IN ARTIFICIAL INTELLIGENCE, EPIA 2013

Páginas: 259-270

16th Portuguese Conference on Artificial Intelligence (EPIA)

Angra do Heroismo, PORTUGAL, SEP 09-12, 2013

Indexação

ISI Web of Knowledge - 5 Citações

Scopus - 6 Citações

Classificação Científica

FOS: Ciências exactas e naturais > Ciências da computação e da informação

Outras Informações

ID Authenticus: P-008-EFP

DOI: 10.1007/978-3-642-40669-0_23

Abstract (EN): Most of the original image feature detectors are not able to cope with large photometric variations, and their extensions that should improve detection eventually increase the computational cost and introduce more noise to the system. Here we extend the original SURF algorithm increasing its invariance to illumination changes. Our approach uses the local space average color descriptor as working space to detect invariant features. A theoretical analysis demonstrates the impact of distinct photometric variations on the response of blob-like features detected with the SURF algorithm. Experimental results demonstrate the effectiveness of the approach in several illumination conditions including the presence of two or more distinct light sources, variations in color, in offset and scale.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 12