Part II Algorithm and System Designs

An increasingly large number of digital binary images have been used in everyday life. Handwritten signatures captured by electronic signing pads are digitally stored and are being used as the records for credit card payment by many department stores in the U.S. and for parcel delivery by major courier services such as the United Parcel Service (UPS). Word processing software like Microsoft Word allows a user to store his/her signature in a binary image file for inclusion at specified locations of a document. The documents signed in such a way can be sent directly to a fax machine or be distributed across a network. The unauthorized use of a signature, such as copying it onto an unauthorized payment, is becoming a big concern. In addition, a variety of important documents, such as social security records, insurance information, and financial documents, have also been digitized and stored. Because it is easy to copy and edit digital images via software tools, the annotation and authentication of binary images as well as the detection of tampering are very important. This chapter discusses data hiding techniques for these purposes as an alternative to or in conjunction with the cryptographic authentication approach. While we expect the 83 CHAPTER 5. DATA HIDING IN BINARY IMAGES 84 embedded data to have some robustness against minor distortion and preferably to withstand printing and scanning, the robustness of embedded data against intentional removal or other obliteration is not a primary concern because there is little incentive to do so in the targeted applications of annotation and authentication. Most prior works on image data hiding are for color or grayscale images in which the pixels may take on a wide range of values. For those images, changing pixel values by a small amount is generally unnoticeable under normal viewing conditions. This property of human visual system plays a key role in watermarking of perceptual media data [44, 46]. For images in which the pixels take on only a limited number of values, hiding data without causing visible artifacts becomes more difficult. In particular, flipping white or black pixels that are not on the boundary is likely to introduce visible artifacts in binary images. Before we present our solutions to the challenging issues of hiding data in binary images, we shall give a brief review of the prior art. Several methods for hiding data in specific types of binary images have …