Loading [a11y]/accessibility-menu.js
Recognition of Low-Resolution Logos in Vehicle Images Based on Statistical Random Sparse Distribution | IEEE Journals & Magazine | IEEE Xplore

Recognition of Low-Resolution Logos in Vehicle Images Based on Statistical Random Sparse Distribution


Abstract:

Traditional image recognition approaches can achieve high performance only when the images have high resolution and superior quality. A new vehicle logo recognition (VLR)...Show More

Abstract:

Traditional image recognition approaches can achieve high performance only when the images have high resolution and superior quality. A new vehicle logo recognition (VLR) method is proposed to treat low-resolution and poor-quality images captured from urban crossings in intelligent transport system, and the proposed approach is based on statistical random sparse distribution (SRSD) feature and multiscale scanning. The SRSD feature is a novel feature representation strategy that uses the correlation between random sparsely sampled pixel pairs as an image feature and describes the distribution of a grayscale image statistically. Multiscale scanning is a creative classification algorithm that locates and classifies a logo integrally, which alleviates the effect of propagation errors in traditional methods by processing the location and classification separately. Experiments show an overall recognition rate of 97.21% for a set of 3370 vehicle images, which showed that the proposed algorithm outperforms classical VLR methods for low-resolution and inferior quality images and is very suitable for on-site supervision in ITSs.
Published in: IEEE Transactions on Intelligent Transportation Systems ( Volume: 16, Issue: 2, April 2015)
Page(s): 681 - 691
Date of Publication: 13 August 2014

ISSN Information:

Funding Agency:


References

References is not available for this document.