Text Detection in Street View Images by Cascaded Convolutional Neural Networks

Considering traffic/shop signs in street view images convey a large amount of information such as locations of pictures taken or effects of advertisement etc., a text detection mechanism for street view images is proposed in this research. To deal with relatively complicated content of street views in urban areas, the proposed scheme consists of two major parts. First, since various interference caused by pedestrians, buildings, vehicles appearing in images will significantly affect the detection performance, a Fully Convolutional Network is employed to locate street signs. Next, another neural network, i.e., Region Proposal Network, will help to extract text lines in the identified traffic/shop signs. Both horizontal and vertical text-lines will be extracted. The experimental results show that the proposed scheme is feasible, especially in processing complex streetscape.