Scene Text Recognition system using multigrain parallelism

We propose a Scene Text Recognition (STR) system for recognizing text contained in natural images. The system is comprehensive of all three steps of STR - text localization, text extraction and text recognition - making it easily applicable to mobile devices. The methods for each step are adopted and tuned from previous works to be more suitable for STR. Since STR is computationally intensive, in order to give faster results to the user, we seek to utilize the computing power of multicore processors. A multigrain parallelism method is proposed which varies the level of parallelism according to task properties and available resources during runtime. The proposed approach was tested on a set of natural scene images and an average speedup factor of 1.72 was achieved when run on a dual core processor. Our multigrain parallelism method can easily be applied to other complex image processing algorithms that work on various units of data.