Detection and Classification of Viewer Age Range Smart Signs at TV Broadcast
This addresses a domain-specific regulatory need for TV broadcast monitoring in Turkey, but it is incremental as it applies existing methods like circle detection and neural networks to a new dataset.
The paper tackled the problem of automatically detecting and classifying Viewer Age Range Smart Signs in TV broadcasts to enable age-sensitive TV receivers, achieving implementation on a standard PC with analysis of circle detection methods and a Multilayer Perceptron for classification.
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.