Handwritten Word Spotting in Old Manuscript Images using Shape ...

6. Preliminary steps
6.1 Pre-processing
Modelling the human cognitive process to obtain a similar computational methodology for handwritten
word segmentation is quite difficult due to the following characteristics. The handwriting
style is usually in cursive or discrete. In the case of discrete handwriting, characters are joined to
form words, but, unlike the machine printed text, handwritten text is not uniformly spaced. The
size of the characters along the words of the document is different (this is a scale problem). Ascenders
and descenders are regularly connected and words present different orientations. Documents
are often degraded due the ageing or other reasons. Another reason is the presence of show-through
or bleed-through effects explained above.
Some of the main problems of our historical documents are that they have been written by
several authors (every two years the writer changes), noisy (stains, shadows, bleed through, etc.),
margins, etc.
The documents to be used in our experiments present some of the above commented drawbacks,
like ascenders and descenders connected, different sizes of character, etc. But a good characteristics
of these documents is that they are well structured. As we have commented in section 2, each
document has three parts, and the objective is to work with the marriage licenses.
The steps of the pre-processing are: binarization of the documents, page segmentation, layout
segmentation, segmentation of the lines and, the last step, the word segmentation (Fig. 6). Let us
in the following subsections describe the details of these steps.
Figure 6: Pre-processing steps.
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