Text Line Segmentation in Handwritten Documents Based on Connected Components Trajectory Generation

Text line segmentation in handwritten documents is an important step in many high level processing such as handwritten document enhancement and text recognition. In this paper we describe a novel approach of text line segmentation based on tracking. In this sense, we consider each connected component in the image as a moving object in its respective line and find its best match given its history motion, i.e. the closest connected component that lie in its trajectory. Direction of motion gives direction of handwritten text and is the output of our tracking algorithm. We apply our approach to images of ICDAR 2013 handwritten segmentation contest and report an overall detection rate of 86.51%.