Image registration by "super-curves".

We solve the 2-D affine image registration problem by curve matching and alignment. Our approach starts with a super-curve, which is formed by superimposing two affine related curves in one coordinate system. We use B-spline fusion technique to find a single B-spline approximation of the super-curve and a registration between the two curves simultaneously. This approach achieves superior accuracy and efficiency in curve matching and alignment. We then address the occlusion problem by finding partial match between the curves segmented using inflections and cusps, which are affine invariant. The combination of edge detection and curve alignment lead to accurate image registration.

Data hiding in image and video: Part I--fundamental issues and solutions.

In this Part I of a two-part paper, we address a number of fundamental issues of data hiding in image and video and propose general solutions to them. We begin with a review of two major types of embedding, based on which we propose a new multilevel embedding framework to allow the amount of extractable data to be adaptive according to the actual noise condition. We then study the issues of hiding multiple bits through a comparison of various modulation and multiplexing techniques. Finally, the nonstationary nature of visual signals leads to highly uneven distribution of embedding capacity and causes difficulty in data hiding. We propose an adaptive solution switching between using constant embedding rate with shuffling and using variable embedding rate with embedded control bits. We verify the effectiveness of our proposed solutions through analysis and simulation. And Part II will apply these solutions to specific design problems for embedding data in grayscale and color images and video.

Data hiding in image and video: Part II--designs and applications.

This paper applies the solutions to the fundamental issues addressed in Part I to specific design problems of embedding data in image and video. We apply multilevel embedding to allow the amount of embedded information that can be reliably extracted to be adaptive with respect to the actual noise conditions. When extending the multilevel embedding to video, we propose strategies for handling uneven embedding capacity from region to region within a frame as well as from frame to frame. We also embed control information to facilitate the accurate extraction of the user data payload and to combat such distortions as frame jitter. The proposed algorithm can be used for a variety of applications such as copy control, access control, robust annotation, and content-based authentication.