Binarisation of Colour Map Images through Extraction of Regions

Abstract

Methods to convert colour images to binary form are already reported in the literature. However, these methods are inadequate for binary conversion of complex documents such as maps due to large intensity variations in different regions and entangled texts with lines representing borders, rivers, roads and other similar components. This paper proposes a new binary conversion technique, for coloured land map images, by extracting the regions and analysing the hue, saturation spread and within class ‘kurtosis’. This is a region-wise adaptive algorithm which copes up with the sharp changes of the discriminating features on different regions. Here, local regions are selected as clusters having the same hues and saturation. These regions are individually converted to binary form using the spread of their degree of within class kurtosis. The individual regions are finally combined. Our experiments include 446 colour maps from the map image database created for this purpose and made freely available at http://code.google.com/p/lmidb .