Segmentation of heterogeneous document images : an ... - Tel

Chapter 3
Text/graphics separation
tel-00912566, version 1 - 2 Dec 2013
Separation of text and graphics in document images is the first step in
our methodology. This is an important stage that not only improves
the results of text region and text line detection by not allowing graphical
drawings to be merged with text regions but also by providing
assistance for separating text regions as we will see in the next chapter.
3.1 Preprocessing
Preprocessing is the first step that happens after reading a document image
into memory. The aim is to prepare the document for text and graphics separation.
Our method works with connected components. Each component can
be a character, punctuation, noise, part of a handwritten word, rule lines or
graphical elements. To extract these components, binarization first takes place.
It is worth noting that different binarization methods exist. When a document
image is in good condition, Otsu’s binarization method performs better than
other methods such as Sauvola [82, 11] or Niblack [68]. The reason is that
Otsu’s method often keeps all parts of graphical drawings in a single piece. On
the other hand Sauvola’s binarization method should be used when dealing with
low quality historical documents or bad lighting conditions. Figure 3.1 shows
a part of a gray-level document with bad lighting condition and compares the
result of binarization by Otsu and Sauvola methods. Figure 3.2 illustrates the
advantage of applying Otsu’s method to documents that contain drawings and
graphical components. After binarization, a connected component analysis can
simply extract all connected components (CCs) of the image.
3.2 Features
As already mentioned in the previous chapter, most methods use either blockbased
or component based approach for labeling components. To clarify this,
if a method is assigning a label {text,graphics} to one component then it tends
to extract component based features such as size, area, etc. And if the method
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