Wavelet applications in segmentation of handwriting in archival documents

Abstract

The National Archives of Singapore keeps a large number of double-sided handwritten archival documents. Over long periods of storage, ink sipped through the pages of these documents, resulting in interfering images of handwriting coming from the back of the page. This paper addresses this problem of segmenting handwriting from both sides of a document by means of a wavelet approach. We first match both sides of a document page such that the interfering strokes are mapped with the corresponding strokes originating from the reverse side. This allows the identification of the foreground and interfering strokes. A wavelet reconstruction process then iteratively enhances the foreground strokes and smears the interfering strokes so as to strengthen the discriminating capability of an improved Canny edge detector against the interfering strokes. Experimental results confirm the validity of the wavelet approach.