Spotting text in a natural scene image is a challenging task. It involves text localization in the image and text recognition given these localized text image patches. To tackle this problem, traditional optical character recognition (OCR) techniques – which are designed specifically for black and white text contents – give way to more sophisticated methods like neural networks.
Yuanhang Su, one MCL member, is now collaborating with Inha University, Korean Airline and Pratt & Whitney institute for collaborative engineering (PWICE) to build a text spotting system. Our lab has developed a comprehensive text spotting system that can localize and recognize text in natural scene images by using combined convolutional neural network (CNN) and recurrent neural network (RNN) architecture. Our system is able to deal with English and Korean text contents.