Title

Street Detection with Asymmetric Haar Features

Authors

Geovany Ramirez, University of Texas at El Paso
Olac Fuentes, University of Texas at El PasoFollow

Publication Date

2012

Document Type

Conference Proceeding

Comments

Ramirez G.A., Fuentes O. (2012) Street Detection with Asymmetric Haar Features. In: Alvarez L., Mejail M., Gomez L., Jacobo J. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2012. Lecture Notes in Computer Science, vol 7441. Springer, Berlin, Heidelberg

https://doi.org/10.1007/978-3-642-33275-3_49

Abstract

We present a system for object detection applied to street detection in satellite images. Our system is based on asymmetric Haar features. Asymmetric Haar features provide a rich feature space, which allows to build classifiers that are accurate and much simpler than those obtained with other features. The extremely large parameter space of potential features is explored using a genetic algorithm. Our system uses specialized detectors in different street orientations that are built using AdaBoost and the C4.5 rule induction algorithm. Experimental results show that Asymmetric Haar features are better than basic Haar features for street detection.