A new regularity based descriptor computed from local image oscillations.
TRUJILLO, Leonardo
Centro de Investigacion Cientifica y de Education Superior de Ensenada [Mexico] [CICESE]
Centro de Investigacion Cientifica y de Education Superior de Ensenada [Mexico] [CICESE]
OLAGUE, Gustavo
Centro de Investigacion Cientifica y de Education Superior de Ensenada [Mexico] [CICESE]
Centro de Investigacion Cientifica y de Education Superior de Ensenada [Mexico] [CICESE]
LEGRAND, Pierrick
Institut de Mathématiques de Bordeaux [IMB]
Artificial Evolution and Fractals [COMPLEX]
See more >
Institut de Mathématiques de Bordeaux [IMB]
Artificial Evolution and Fractals [COMPLEX]
TRUJILLO, Leonardo
Centro de Investigacion Cientifica y de Education Superior de Ensenada [Mexico] [CICESE]
Centro de Investigacion Cientifica y de Education Superior de Ensenada [Mexico] [CICESE]
OLAGUE, Gustavo
Centro de Investigacion Cientifica y de Education Superior de Ensenada [Mexico] [CICESE]
Centro de Investigacion Cientifica y de Education Superior de Ensenada [Mexico] [CICESE]
LEGRAND, Pierrick
Institut de Mathématiques de Bordeaux [IMB]
Artificial Evolution and Fractals [COMPLEX]
< Reduce
Institut de Mathématiques de Bordeaux [IMB]
Artificial Evolution and Fractals [COMPLEX]
Language
en
Article de revue
This item was published in
Optics Express. 2007, vol. 15, n° 10, p. 6140-6145
Optical Society of America - OSA Publishing
English Abstract
This work presents a novel local image descriptor based on the concept of pointwise signal regularity. Local image regions are extracted using either an interest point or an interest region detector, and discriminative ...Read more >
This work presents a novel local image descriptor based on the concept of pointwise signal regularity. Local image regions are extracted using either an interest point or an interest region detector, and discriminative feature vectors are constructed by uniformly sampling the pointwise Holderian regularity around each region center. Regularity estimation is performed using local image oscillations, the most straightforward method directly derived from the definition of the Holder exponent. Furthermore, estimating the Holder exponent in this manner has proven to be superior when compared to wavelet based estimation. Our detector shows invariance to illumination change, JPEG compression, image rotation and scale change. Results show that the proposed descriptor is stable with respect to variations in imaging conditions, and reliable performance metrics prove it to be comparable and in some instances better than SIFT, the state-of-the-art in local descriptors.Read less <
Origin
Hal imported