  Today all kind of information is getting digitized and along with all this
digitization, the huge archive of various kinds of documents is being digitized
too. We know that, Optical Character Recognition is the method through which,
newspapers and other paper documents convert into digital resources. But, it is
a fact that this method works on texts only. As a result, if we try to process
any document which contains non-textual zones, then we will get garbage texts
as output. That is why; in order to digitize documents properly they should be
prepossessed carefully. And while preprocessing, segmenting document in
different regions according to the category properly is most important. But,
the Optical Character Recognition processes available for Bangla language have
no such algorithm that can categorize a newspaper/book page fully. So we worked
to decompose a document into its several parts like headlines, sub headlines,
columns, images etc. And if the input is skewed and rotated, then the input was
also deskewed and de-rotated. To decompose any Bangla document we found out the
edges of the input image. Then we find out the horizontal and vertical area of
every pixel where it lies in. Later on the input image was cut according to
these areas. Then we pick each and every sub image and found out their
height-width ratio, line height. Then according to these values the sub images
were categorized. To deskew the image we found out the skew angle and de skewed
the image according to this angle. To de-rotate the image we used the line
height, matra line, pixel ratio of matra line.
