Publications

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.

BibTeX

@inproceedings{CCCSSWWN11,
  author    = {Adam Coates and Blake Carpenter and Carl Case and
               Sanjeev Satheesh and Bipin Suresh and Tao Wang and
               David J. Wu and Andrew Y. Ng},
  title     = {Text Detection and Character Recognition in Scene Images with Unsupervised Feature Learning},
  booktitle = {International Conference on Document Analysis and Recognition ({ICDAR})},
  year      = {2011}
}

Publications

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

Resources