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A comparison of Haar-like, LBP and HOG approaches to concrete and asphalt runway detection in high resolution imagery

doi: 10.6062/jcis.2015.06.03.0101

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Juliano E. C. Cruz, Elcio H. Shiguemori and Lamartine N. F. Guimarães


In this article, the three most used object detection approaches, Linear Binary Pattern cascade, Haarlike cascade, and Histogram of Oriented Gradients with Support Vector Machine are applied to automatic runway detection in high resolution satellite imagery and their results are compared. They have been employed predominantly for human feature recognition and this paper tests theirs applicability to runways. The results show that they can be indeed employed for this purpose with LBP and Haar approaches performing better than HOG+SVM.


Runway detection, satellite imagery, boosting, boosted cascade, LBP, Haar-like, HOG, SVM, com- putational mathematics.


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