Binarization of a static signature image: preprocessing and its quality assessment

In the paper we present a comparative study of binarization methods for color images of static signatures made with ballpoint pens of different types and colors. Signature image binarization is the first step before calculating its features and verification. Because of the uneven flow of ink from ballpoint pens, images of signatures made with such pens present particular challenges. A comparison of digital signature image preprocessing methods aimed at preserving the shape of the signature lines in the binary representations is conducted. A comparative analysis of binarization methods for color signature images is performed based on four methods from different classes: global thresholding (Otsu, Kapura), locally adaptive thresholding (Sauvola), and a method of direct indexing the RGB color space into two classes: white and black pixels. For the first time, empirical objective criteria for the quality of a binary signature representation in the absence of a reference are proposed, based on the analysis of connected components and the skeleton of the binary signature representation. Experiments were performed on images from the publicly available CEDAR database and a database of signatures collected during the research. It has been shown that Kapur's method provides the best preservation of signature form in its binary representation, outperforming other methods, including the popular Otsu method. We propose a four-step procedure for generating a binary signature representation. This procedure consists of scanning a color signature at 300 or 600 DPI in the RGB model, converting the color image to grayscale using principal component analysis (PCA), binarization by the Kapoor method, and post-processing the binary image. This method is intended for developing static signature verification systems.

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