Tree structure for word extraction from handwritten text lines

Word extraction from handwritten text lines usually involves the calculation of a line specific threshold which separates the gaps between words from the gaps inside the words in that line. We show that this approach can be improved if the decision about a gap is not only made in terms of a threshold, but also depends on the context of that gap, i.e. if the relative sizes of the surrounding gaps are taken into consideration. For this purpose, we propose to build a structure tree of the text line, whose nodes represent possible word candidates. Such a tree is traversed in a top-down manner to find the nodes that correspond to words of the text line. Experiments with different gap metrics as well as threshold types show that the new method can yield significant improvements over conventional word extraction methods.