WSEAS Transactions on Signal Processing
Print ISSN: 1790-5052, E-ISSN: 2224-3488
Volume 14, 2018
Muti-Scale Feature Extraction for Vehicle Detection Using PHis-LBP
Authors: , , , ,
Abstract: Multi-resolution object detection faces several drawbacks including its high dimensionality produced by a richer image representation in different channels or scales. In this paper, we propose a robust and lightweight multi-resolution method for vehicle detection using local binary patterns (LBP) as channel feature. Algorithm acceleration is done using LBP histograms instead of multi-scale feature maps and by extrapolating nearby scales to avoid computing each scale. We produce a feature descriptor capable of reaching a similar precision to other computationally more complex algorithms but reducing its size from 10 to 800 times. Finally, experiments show that our method can obtain accurate and considerably faster performance than state-of-the-art methods on vehicles datasets.
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Pages: 91-98
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 14, 2018, Art. #12