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

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 mac... Authors: Adam Coates, Blake Carpenter, Carl Case, Sanjeev Satheesh, Bipin Suresh, Tao Wang, David Wu, Andrew Y. Ng (2011)
AUTHORED BY
Adam Coates
Blake Carpenter
Carl Case
Sanjeev Satheesh
Bipin Suresh
Tao Wang
David Wu
Andrew Y. Ng

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. Keywords-Robust reading, character recognition, feature learning, photo OCR
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