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title: "Adaptive Binarisation"
-date: 2019-10-02
+date: 2019-12-17
draft: true
categories: [binarisation, preprocessing, image manipulation]
+The [previous post](/posts/binarisation-introduction) covered the
+basics of binarisation, and introduced the Otsu algorithm, a good
+method for finding a global threshold number for a page. But there
+are inevitable limitations with using a global threshold for
+binarisation. Better would be to use a threshold that is adapted
+over different regions of the page, so that as the conditions of the
+page change so can the threshold. This technique is called adaptive
+For each pixel of an image, adaptive binarisation considers the
+pixels around it to determine a good threshold. This means that even
+in an area which is heavily shaded, for example near the spine of a
+book, the text will be correctly differentiated from the background,
+as even though they may both be darker than the text in the rest of
+the page, it is the darkness relative to its surroundings that
+(diagram showing 2 different areas of a page, one light and one dark,
+comparing global and local thresholding [can be fake, as the global
+threshold diagram was])
+(actually can probably just have a dark area of a page, comparing global
+and local thresholding, setting the global one such that the image is
+screwed up)