IAM-OnDB - an On-Line English Sentence Database Acquired from Handwritten Text on a Whiteboard

In this paper we present IAM-OnDB - a new large online handwritten sentences database. It is publicly available and consists of text acquired via an electronic interface from a whiteboard. The database contains about 86 K word instances from an 11 K dictionary written by more than 200 writers. We also describe a recognizer for unconstrained English text that was trained and tested using this database. This recognizer is based on Hidden Markov Models (HMMs). In our experiments we show that by using larger training sets we can significantly increase the word recognition rate. This recognizer may serve as a benchmark reference for future research.

• Type: Conference
• Year: 2005
• Where: ICDAR
• Authors: Marcus Liwicki, Horst Bunke
• Keywords: Document Analysis, Handwritten Sentences Database, ICDAR 2005, Recognizer, Unconstrained English Text