Text Detection and Character Recognition in Scene Images with Unsupervised Feature Learning

This paper applies large-scale algorithms for learning the features automatically from unlabeled data to construct highly effective classifiers for both detection and recognition to be used in a high accuracy end-to-end system.

Abstract

Reading text from photographs is a challenging problem that has received a significant amount of attention. Two key components of most systems are (i) text detection from images and (ii) character recognition, and many recent methods have been proposed to design better feature representations and models for both. In this paper, we apply methods recently developed in machine learning -- specifically, large-scale algorithms for learning the features automatically from unlabeled data -- and show that they allow us to construct highly effective classifiers for both detection and recognition to be used in a high accuracy end-to-end system.