This program reproduces the results of the Baseline (CV3 + Tess) reported in the ICDAR2015 Robust Reading Competition.
Created on: May 3, 2015 Author: Lluis Gomez i Bigorda
The "Baseline (OpenCV + Tesseract)" makes use of the publicly available pipeline proposed in . Concretely, among the available algorithms in the OpenCV text module, we use the Class Specific Extremal Regions (CSER) and Exhaustive Search algorithms initially proposed by Neumann and Matas [2,3] along with the perceptual grouping approach of Gomez and Karatzas  for text localisation. We apply to the output of this pipeline, the open source Tesseract OCR engine to perform text recognition.
 L. Gomez and D. Karatzas, "Scene text recognition: No country for old men?" in Computer Vision-ACCV 2014 Workshops. Springer, 2014, pp. 157–168.
 L. Neumann and J. Matas, "Real-time scene text localization and recognition," in Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on. IEEE, 2012, pp. 3538–3545.
 L. Neumann and J. Matas, "Text Localization in Real-world Images using Efficiently Pruned Exhaustive Search, ICDAR 2011 (Beijing, China)
 L. Gomez and D. Karatzas, "Multi-script text extraction from natural scenes," in Document Analysis and Recognition (ICDAR), 2013 12th International Conference on. IEEE, 2013, pp. 467–471.