Handwritten Text Recognition (HTR) system implemented with TensorFlow (TF) and trained on the IAM off-line HTR dataset. The model takes images of single words or text lines (multiple words) as input and outputs the recognized text. 3/4 of the words from the validation-set are correctly recognized, and the character error rate is around 10%.

Follow these instructions to get the IAM dataset:

• Register for free at this website
• Download words/words.tgz
• Download ascii/words.txt
• Create a directory for the dataset on your disk, and create two subdirectories: img and gt
• Put words.txt into the gt directory
• Put the content (directories a01, a02, ...) of words.tgz into the img directory

It consists of 5 CNN layers, 2 RNN (LSTM) layers and the CTC loss and decoding layer.

• Build a Handwritten Text Recognition System using TensorFlow
• Scheidl - Handwritten Text Recognition in Historical Documents
• Scheidl - Word Beam Search: A Connectionist Temporal Classification Decoding Algorithm