Ming Sun Fu

Bio: Ming Sun Fu is an academic researcher from Hong Kong University of Science and Technology. The author has contributed to research in topics: Halftone & Digital watermarking. The author has an hindex of 14, co-authored 27 publications receiving 805 citations. Previous affiliations of Ming Sun Fu include University of Hong Kong.

Data hiding watermarking for halftone images

Abstract: In many printer and publishing applications, it is desirable to embed data in halftone images. We proposed some novel data hiding methods for halftone images. For the situation in which only the halftone image is available, we propose data hiding smart pair toggling (DHSPT) to hide data by forced complementary toggling at pseudo-random locations within a halftone image. The complementary pixels are chosen to minimize the chance of forming visually undesirable clusters. Our experimental results suggest that DHSPT can hide a large amount of hidden data while maintaining good visual quality. For the situation in which the original multitone image is available and the halftoning method is error diffusion, we propose the modified data hiding error diffusion (MDHED) that integrates the data hiding operation into the error diffusion process. In MDHED, the error due to the data hiding is diffused effectively to both past and future pixels. Our experimental results suggest that MDHED can give better visual quality than DHSPT. Both DHSPT and MDHED are computationally inexpensive.

Data hiding in halftone images by stochastic error diffusion

Abstract: We propose a novel method called DHSED (data hiding stochastic error diffusion) to hide binary visual patterns in two error diffused halftone images. While one halftone image is only a regular error diffused image, stochastic error diffusion is applied to the other image to generate special stochastic characteristics with respect to the first image such that the visual pattern would appear when the two halftone images are overlaid Simulation results show that the two halftone images have good visual quality, and the hidden pattern appears with "normal" and "lower-than-normal" intensity when the two halftone images are overlaid.

Methods and apparatus for hiding data in halftone images

Abstract: We propose methods for generating a halftone image, in which each pixel takes one of two tone values. The generated image contains hidden data, which is present at data storage pixels chosen using a pseudo-random number generator. In a first case, the data is hidden within an existing halftone image by reversing the tone value at certain of the data storage pixels, and at pixels neighbouring the data storage pixels. In a second case, the halftone image is generated from a grey-scale image, and data is hidden during this conversion process.

Data hiding by smart pair toggling for halftone images

Abstract: There is growing interest in hiding data for authentication and copyright control in halftone images printed in books, newspapers and by computer printers. A previous data hiding method, the data hiding by pair-toggling (DHPT), is reasonably good but introduce considerable visual artifacts. In this paper, we analyze the sources of the artifacts in DHPT and propose an improvement by using smart pair toggling. Simulation results suggest that the proposed data hiding by smart pair-toggling (DHSPT) algorithm can hide the same amount of data while generating halftone images with considerably better visual quality than DHPT.

Data Hiding for halftone images

Abstract: With the ease of distribution of digital images, there is a growing concern for copyright control and authentication. While there are many existing watermarking and data hiding methods for natural images, almost none can be applied to halftone images. In this paper, we proposed two novel data hiding methods for halftone images. The proposed Data Hiding Pair-Toggling (DHPT) hides data by forced complementary toggling at pseudo-random locations within a halftone image. It is found to be very effective for halftone images with relatively coarse textures. For halftone images with fine textures (such as error diffusion with Steinberg kernel), the proposed Data Hiding Error Diffusion (DHED) gives significantly better visual quality by integrating the data hiding into the error diffusion operation. Both DHPT and DHED are computationally very simple and yet effective in hiding a relatively large amount of data. Both algorithms yield halftone images with good visual quality.

Digital Watermarking

Abstract: Digital watermarking is a key ingredient to copyright protection. It provides a solution to illegal copying of digital material and has many other useful applications such as broadcast monitoring and the recording of electronic transactions. Now, for the first time, there is a book that focuses exclusively on this exciting technology. Digital Watermarking covers the crucial research findings in the field: it explains the principles underlying digital watermarking technologies, describes the requirements that have given rise to them, and discusses the diverse ends to which these technologies are being applied. As a result, additional groundwork is laid for future developments in this field, helping the reader understand and anticipate new approaches and applications.

Digital Watermarking and Steganography

Abstract: Digital audio, video, images, and documents are flying through cyberspace to their respective owners. Unfortunately, along the way, individuals may choose to intervene and take this content for themselves. Digital watermarking and steganography technology greatly reduces the instances of this by limiting or eliminating the ability of third parties to decipher the content that he has taken. The many techiniques of digital watermarking (embedding a code) and steganography (hiding information) continue to evolve as applications that necessitate them do the same. The authors of this second edition provide an update on the framework for applying these techniques that they provided researchers and professionals in the first well-received edition. Steganography and steganalysis (the art of detecting hidden information) have been added to a robust treatment of digital watermarking, as many in each field research and deal with the other. New material includes watermarking with side information, QIM, and dirty-paper codes. The revision and inclusion of new material by these influential authors has created a must-own book for anyone in this profession. *This new edition now contains essential information on steganalysis and steganography *New concepts and new applications including QIM introduced *Digital watermark embedding is given a complete update with new processes and applications

Image steganographic scheme based on pixel-value differencing and LSB replacement methods

Abstract: In order to improve the capacity of the hidden secret data and to provide an imperceptible stego-image quality, a novel steganographic method based on least-significant-bit (LSB) replacement and pixel-value differencing (PVD) method is presented. First, a different value from two consecutive pixels by utilising the PVD method is obtained. A small difference value can be located on a smooth area and the large one is located on an edged area. In the smooth areas, the secret data is hidden into the cover image by LSB method while using the PVD method in the edged areas. Because the range width is variable, and the area in which the secret data is concealed by LSB or PVD method are hard to guess, the security level is the same as that of a single using the PVD method of the proposed method. From the experimental results, compared with the PVD method being used alone, the proposed method can hide a much larger information and maintains a good visual quality of stego-image.

Halftone Visual Cryptography Via Error Diffusion

Abstract: Halftone visual cryptography (HVC) enlarges the area of visual cryptography by the addition of digital halftoning techniques. In particular, in visual secret sharing schemes, a secret image can be encoded into halftone shares taking meaningful visual information. In this paper, HVC construction methods based on error diffusion are proposed. The secret image is concurrently embedded into binary valued shares while these shares are halftoned by error diffusion-the workhorse standard of halftoning algorithms. Error diffusion has low complexity and provides halftone shares with good image quality. A reconstructed secret image, obtained by stacking qualified shares together, does not suffer from cross interference of share images. Factors affecting the share image quality and the contrast of the reconstructed image are discussed. Simulation results show several illustrative examples.