Detection and Classification of Viewer Age Range Smart Signs at TV Broadcast

TL;DR

This paper presents a method for automatic detection and classification of Viewer Age Range Smart Signs in TV broadcasts using circle detection and neural networks, enabling smarter TV receivers.

Contribution

It introduces a combined approach of circle detection and neural network classification for real-time identification of age range signs in broadcast videos.

Findings

Effective circle detection methods analyzed and compared.

Neural network successfully classifies age signs in still images and videos.

Implementation achieved on standard PC in real-time.

Abstract

In this paper, the identification and classification of Viewer Age Range Smart Signs, designed by the Radio and Television Supreme Council of Turkey, to give age range information for the TV viewers, are realized. Therefore, the automatic detection at the broadcast will be possible, enabling the manufacturing of TV receivers which are sensible to these signs. The most important step at this process is the pattern recognition. Since the symbols that must be identified are circular, various circle detection techniques can be employed. In our study, first, two different circle segmentation methods for still images are analyzed, their advantages and drawbacks are discussed. A popular neural network structure called Multilayer Perceptron is employed for the classification. Afterwards, the same procedures are carried out for streaming video. All of the steps depicted above are realized on a standard PC.