Distance transform based text-line extraction from unconstrained handwritten document images

Abstract

Text-line extraction (TLE) is the process of segmenting a document page into lines of text for processing by modules such as language and writer identification or Optical Character Recognition (OCR). Designing of an appropriate TLE method is always a challenging research problem especially in the domain of unconstrained handwritten documents. This is because of the vast number of potential interactions between the text lines. For example, these lines are not always straight, lines written close to each other can overlap with ascenders and descenders, and lines can interact with other content on the page. In this paper, we present a novel language-independent text-line extraction method for unconstrained handwritten documents which handles complexities such as touching and multi-skewed text lines, overlapping characters and irregular inter-line spacing. Our method preprocesses the document pages using a distance transform based method and uses a novel path detection algorithm to separate individual text-line. The proposed method has been tested on six standard datasets which are publicly available and the experimental results show that our method achieves a promising accuracy over state-of-the-art TLE methods.