A Survey on Word Segmentation Method for Handwritten Documents

One of the most important and challenging tasks in a handwritten recognition pipeline is the segmentation of handwritten document images into text lines and words. Several problems inherent in handwritten documents such as the difference in the skew angle between text lines or along the same text line, the existence of adjacent text lines or words touching, the existence of characters with different sizes and variable intra-word gaps seriously affect the segmentation and, consequently, the recognition accuracy. Therefore, it is imperative to have a benchmarking dataset along with an objective evaluation methodology in order to capture the efficiency of current and new practices in handwritten document segmentation.