Title :
A comparison study on motorcycle license plate detection
Author :
Gee-Sern Hsu ; Si-De Zeng ; Chun-Wei Chiu ; Sheng-Luen Chung
Author_Institution :
Nat. Taiwan Univ. of Sci. & Technol. (NTUST), Taipei, Taiwan
fDate :
June 29 2015-July 3 2015
Abstract :
License plate detection and recognition are mostly studied on automobiles but only few on motorcycles. As motorcycles are becoming popular for local transportation and environmental friendliness, the demands for license plate recognition have been increasing in recent years. The primary difference between the license plate recognition in automobiles and motorcycles is on the detection of license plates, which is the topic of this study. For automobiles, the license plates are mostly installed on the front or on the back of the vehicle with relatively less complicated backgrounds; however, for motorcycles, the backgrounds can be far more complicated. To better handle complicated backgrounds, we study the case with motorcycle detection as preprocessing so that the search area for the license plate can be better constrained, and compare its performance with the case without the preprocessing. A few detection methods are configured and studied for both the motorcycle detection and license plate detection, including the state-of-the-art part-based model. Considering processing speed and accuracy, the histogram of oriented gradients (HOG) with support vector machines (SVMs) is found to be the best detector for motorcycle license plates.
Keywords :
automobiles; motorcycles; object detection; support vector machines; traffic engineering computing; SVM; automobiles; environmental friendliness; histogram of oriented gradients; license plate recognition; local transportation; motorcycle detection; motorcycle license plate detection; motorcycles; support vector machines; Automobiles; Databases; Detectors; Feature extraction; Histograms; Licenses; Motorcycles; Histogram of Oriented Gradients; License Plate Detection; Object Detection; Part-based Model;
Conference_Titel :
Multimedia & Expo Workshops (ICMEW), 2015 IEEE International Conference on
Conference_Location :
Turin
DOI :
10.1109/ICMEW.2015.7169772