Digital Enhancement of Palm Leaf Manuscript Images using Normalization Techniques

Palm leaves were one of the earliest forms of writing media and their use as writing material in South and Southeast Asia has been recorded from as early as the fifth century B.C. until as recently as the late 19th century. Palm leaf manuscripts relating to art and architecture, mathematics, astronomy, astrology, and medicine dating back several hundreds of years are still available for reference today thanks to many ongoing efforts for preservation of ancient documents by libraries and universities around the world. Palm leaf manuscripts typically last a few centuries but with time the palm leaves degrade and the writing becomes illegible to be useful in any form. Image processing techniques can help enhance the images of these manuscripts so as to enable retrieval of the written text from these degraded documents. In this paper we propose a transform based method for enhancing digital images of palm leaf manuscripts. The method uses a dynamically selected pivoting background color in a linear transform to enhance the legibility of the foreground text. Then a combination of two other image processing algorithms viz., histogram normalization and background normalization developed in our earlier research, are applied to the transformed image. The algorithms can be mathematically combined into one or two transformations for computational efficiency. The method is tested on a set of palm leaf images from various sources and the preliminary results show significant improvement in readability. The techniques can also be used to enhance images of ancient, historical, degraded papyrus and paper documents.