Ming Sun Fu

Data hiding watermarking for halftone images

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 by smart pair toggling for halftone images

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

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.

Steganography in halftone images: conjugate error diffusion

In this paper, we propose a method called data hiding by conjugate error diffusion (DHCED) to hide an invisible binary visual pattern in two or more error diffused halftone images, which can be from the same or different multi-tone images. In DHCED, distortions of limited magnitude are added to the multi-tone image such that the pixel values of the various halftone images tend to be conjugate to each other. With the conjugate relationship, the dark regions of the hidden pattern would appear on the halftone images when they are overlaid. Simulation results show that the DHCED watermarked halftone images have good visual quality, and the hidden pattern is revealed with good contrast when the watermarked halftone images are overlaid. Even better contrast can be achieved when more than two watermarked halftone images are used.

Joint visual cryptography and watermarking

In this paper, we discuss how to use the watermarking technique for visual cryptography. Both halftone watermarking and visual cryptography involve a hidden secret image. However, their concepts are different. For visual cryptography, a set of shared binary images is used to protect the content of the hidden image. The hidden image can only be revealed when enough shared images are obtained. For watermarking, the hidden image is usually embedded in a single halftone image while preserving the quality of the watermarked halftone image. In this paper, we propose a joint visual-cryptography and watermarking (JVW) algorithm that has the merits of both visual cryptography and watermarking

Halftone image data hiding with intensity selection and connection selection

In this paper, we propose two novel algorithms, namely intensity selection (IS) and connection selection (CS), that can be applied to the existing halftone image data hiding algorithms DHSPT, DHPT and DHST to achieve improved visual quality. The proposed algorithms generalize the hidden data representation and select the best location out of a set of candidate locations for the application of DHSPT, DHPT or DHST. The two algorithms provide trade-off between visual quality and computational complexity. The IS yields higher visual quality but requires either the original multi-tone image or the inverse-halftoned image which implies high computation requirement. The CS has lower visual quality than IS but requires neither the original nor the inverse-halftoned images. Some objective visual quality measures are defined. Our experiments suggest that significant improvement in visual quality can be achieved, especially when the number of candidate locations is large.

Hiding data in halftone image using modified data hiding error diffusion

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 a novel data hiding method, Modified Data Hiding Ordered Dithering (MDHED) for halftone images. MDHED is an effective method to hide a relative amount of data while yielding halftone images with good visual quality. Besides, the amount of hidden data is easy to control and the security depends on the key not the system itself.

A novel method to embed watermark in different halftone images: data hiding by conjugate error diffusion (DHCED)

In this paper, we propose a novel way called DHCED to hide invisible patterns in two or more visually different halftone images (e.g. Lena and Harbor) such that the hidden patterns would appear on the halftone images when they are overlaid. Conjugate error diffusion is used to embed the binary visual pattern in the two distinct halftone images. Simulation results show that the two halftone images have good visual quality, and the hidden pattern is visible when the two distinct halftone images are overlaid.

A robust public watermark for halftone images

In many printing and publishing applications, it is desirable to embed data in halftone images for copyright control and authentication purposes. While intentional attacks on printed matter may not be likely, unintentional attacks such as cropping and distortion due to dirt or human writing/marking are likely. In this paper, we proposed a novel halftone image watermarking method called Watermarking Error Diffusion (WED) to embed a robust, invisible, public watermark in the parity domain of halftone images during halftoning while introducing minimal distortion. Since WED uses the local stochastic properties of the halftone image to embed the watermark throughout the whole image, WED is robust to cropping and distortion due to dirt or human writing/marking. Experimental results suggest that WED can give halftone images with good visual quality and the watermark is robust to crop and human marking.

Hybrid inverse halftoning using adaptive filtering

We propose a novel fast inverse halftoning technique using a combination of spatial varying filtering and spatial invariant filtering. The proposed algorithm is significantly simpler than most existing algorithms. Without explicit edge region classification, the proposed spatial varying filter is shown to be capable of preserving edges effectively.