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

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tel-00912566, version 1 - 2 Dec 2013<br />

Figure 2.12: Left image shows segmented lines from a <strong>document</strong> in [7] <strong>an</strong>d Right<br />

image displays projection pr<strong>of</strong>iles <strong>of</strong> vertical strips.<br />

segmentation contests.<br />

Hough-based methods c<strong>an</strong> also be considered as projection based methods.<br />

They are based on Hough tr<strong>an</strong>sform but instead <strong>of</strong> projecting pixel values into<br />

x or y axis, they project intensities onto parameter’s space. In general, the<br />

purpose <strong>of</strong> Hough tr<strong>an</strong>sform is to find imperfect inst<strong>an</strong>ces <strong>of</strong> objects within a<br />

certain class <strong>of</strong> shapes by a voting procedure. The classical Hough tr<strong>an</strong>sform is<br />

concerned with the identification <strong>of</strong> lines in <strong>an</strong> image, <strong>an</strong>d text lines in the case<br />

<strong>of</strong> <strong>document</strong> image. However, it is not limited to lines, <strong>an</strong>d <strong>an</strong>y kind <strong>of</strong> shape<br />

c<strong>an</strong> be found inside <strong>an</strong> image. In <strong>document</strong> image <strong>an</strong>alysis, Hough tr<strong>an</strong>sform<br />

is used in a variety <strong>of</strong> situations. Some methods use it to detect text lines or<br />

the skew <strong>an</strong>gle <strong>of</strong> the text lines, or to drive different characteristics such as the<br />

direction <strong>of</strong> a connected h<strong>an</strong>dwritten word, or even to detect table lines. Here<br />

we note two methods that use Hough tr<strong>an</strong>sform specifically for detecting text<br />

lines.<br />

In [58], G. Louloudis et al. have proposed a Hough tr<strong>an</strong>sform based h<strong>an</strong>dwritten<br />

segmentation method. Their earliest results have been published in<br />

[56, 57]. The method is adapted to deal with challenges <strong>of</strong> h<strong>an</strong>dwritten <strong>document</strong>s,<br />

including arbitrary sl<strong>an</strong>ted <strong>an</strong>d skewed text lines, accent marks above<br />

or below the text lines <strong>an</strong>d touching lines. After dividing the <strong>document</strong> image<br />

into equally sized blocks, the aim <strong>of</strong> Hough tr<strong>an</strong>sform becomes to find domin<strong>an</strong>t<br />

direction <strong>of</strong> connected components in each block. The algorithm also keeps<br />

track <strong>of</strong> the domin<strong>an</strong>t direction <strong>of</strong> all components inside the <strong>document</strong>. To form<br />

text lines, for each connected component a decision is held based on rules that<br />

compare the direction <strong>of</strong> each component in a block with its adjacent blocks.<br />

An additional constraint is applied upon which, a text line is valid only if the<br />

corresponding skew <strong>an</strong>gle <strong>of</strong> the line deviates from the domin<strong>an</strong>t direction by<br />

30

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