Automatic text detection for mobile augmented reality translation

We present a fast automatic text detection algorithm devised for a mobile augmented reality (AR) translation system on a mobile phone. In this application, scene text must be detected, recognized, and translated into a desired language, and then the translation is displayed overlaid properly on the real-world scene. In order to offer a fast automatic text detector, we focused our initial search to find a single letter. Detecting one letter provides useful information that is processed with efficient rules to quickly find the reminder of a word. This approach allows for detecting all the contiguous text regions in an image quickly. We also present a method that exploits the redundancy of the information contained in the video stream to remove false alarms. Our experimental results quantify the accuracy and efficiency of the algorithm and show the strengths and weaknesses of the method as well as its speed (about 160 ms on a recent generation smartphone, not optimized). The algorithm is well suited for real-time, real-world applications.