Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Application of machine learning approach in detection and classification of cars of an image

Application of machine learning approach in detection and classification of cars of an image Support vector machine (SVM) qualified on histogram orientation gradients (HOG) features is a genuine standard across many visual awareness responsibilities. Due to the change in the illumination and scene complexity, moving vehicle detection has become one of the very important components. Therefore, in this paper, a HOG feature descriptor is proposed. HOG features are not perceptive to illumination change and performance is better in characterising object shape and appearance. A feature vector is built by combining all the HOG features, which are required to train a linear SVM classifier for classification of vehicles. Keywords: classification; HOG features; machine learning; SVM classifier; vehicle detection. Reference to this paper should be made as follows: Ashwini, B. and Yuvaraju, B.N. (2017) `Application of machine learning approach in detection and classification of cars of an image', Int. J. Signal and Imaging Systems Engineering, Vol. 10, Nos. 1/2, pp.8­13. Biographical notes: B. Ashwini working as an Associate Professor in Department of Information Science and Engg. at NMAMIT, Nitte, India. Her research interest is image processing, computer vision, data mining. B.N. Yuvaraju is working as a Professor in Department of Computer Science and Engineering at NIE, Mysore, India. His research interest is data mining, http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Signal and Imaging Systems Engineering Inderscience Publishers

Application of machine learning approach in detection and classification of cars of an image

Download PDF
6 pages

Loading next page...
 
/lp/inderscience-publishers/application-of-machine-learning-approach-in-detection-and-yWdKt2iOZj

References

References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.

Publisher
Inderscience Publishers
Copyright
Copyright © 2017 Inderscience Enterprises Ltd.
ISSN
1748-0698
eISSN
1748-0701
DOI
10.1504/IJSISE.2017.084564
Publisher site
See Article on Publisher Site

Abstract

Support vector machine (SVM) qualified on histogram orientation gradients (HOG) features is a genuine standard across many visual awareness responsibilities. Due to the change in the illumination and scene complexity, moving vehicle detection has become one of the very important components. Therefore, in this paper, a HOG feature descriptor is proposed. HOG features are not perceptive to illumination change and performance is better in characterising object shape and appearance. A feature vector is built by combining all the HOG features, which are required to train a linear SVM classifier for classification of vehicles. Keywords: classification; HOG features; machine learning; SVM classifier; vehicle detection. Reference to this paper should be made as follows: Ashwini, B. and Yuvaraju, B.N. (2017) `Application of machine learning approach in detection and classification of cars of an image', Int. J. Signal and Imaging Systems Engineering, Vol. 10, Nos. 1/2, pp.8­13. Biographical notes: B. Ashwini working as an Associate Professor in Department of Information Science and Engg. at NMAMIT, Nitte, India. Her research interest is image processing, computer vision, data mining. B.N. Yuvaraju is working as a Professor in Department of Computer Science and Engineering at NIE, Mysore, India. His research interest is data mining,

Journal

International Journal of Signal and Imaging Systems Engineering – Inderscience Publishers

Published: Jan 1, 2017

There are no references for this article.