The Application of a Convolution Neural Network on Face and License Plate Detection

Author

Chen, Ying-Nong ; Han, Chin-Chuan ; Wang, Cheng-Tzu ; Jeng, Bor-Shenn ; Fan, Kuo-Chin

Author_Institution

Dept. of Comput. Sci. & Inf. Eng., Nat. Central Univ., Shuanglianpo

Volume

3

fYear

0

fDate

0-0 0

Firstpage

552

Lastpage

555

Abstract

In this paper, two detectors, one for face and the other for license plates, are proposed, both based on a modified convolutional neural network (CNN) verifier. In our proposed verifier, a single feature map and a fully connected MLP were trained by examples to classify the possible candidates. Pyramid-based localization techniques were applied to fuse the candidates and to identify the regions of faces or license plates. In addition, geometrical rules filtered out false alarms in license plate detection. Some experimental results are given to show the effectiveness of the approach

Keywords

face recognition; learning (artificial intelligence); multilayer perceptrons; object detection; self-organising feature maps; vehicles; convolutional neural network verifier; face detection; geometrical rules; license plate detection; multilayer perceptron training; pyramid-based localization; Computer science; Computer vision; Convolution; Detectors; Face detection; Feature extraction; Histograms; Humans; Licenses; Neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2006. ICPR 2006. 18th International Conference on

Conference_Location

Hong Kong

ISSN

1051-4651

Print_ISBN

0-7695-2521-0

Type

conf

DOI

10.1109/ICPR.2006.1115

Filename

1699586