Research And Improvement On The Image Deformation

Image deformation algorithm has been focused on and researched for many years. It is a useful tool various application such as film and cartoon maker, image editing, enriching graphical user interfaces and controlling of face or action. This paper connecting with the requirement of company discusses the latest two image deformation algorithms: image deformation using moving least squares and 2D shape deformation using non-linear least squares optimization.First, the paper will discuss the MLS algorithm which uses linear function to map points in the undeformed image to the deformed image. These functions contain affine, similarity and rigid transformations. These deformations are real and give the user the impression of manipulation real-world objects. The design of system also allows the user to specify the deformations using either sets of points or line segments, the later useful for controlling curves and profiles present in the image. The paper will introduce the deformation controlling by points and lines. Rigid transformation has the best result in all the three deformations.Then, the paper will do advanced research on another method of deformation nonlinear least squares optimization. The novel algorithm aims to preserve two geometric properties of 2D shapes: the Laplacian coordinates of the boundary curve of the shape and local areas inside the shape. Besides preserving local shape properties, this paper also introduce a scheme to preserve the global area of the shape which is useful for deforming incompressible objects.At last, the paper bases on triangle mesh, preserving the length of edges during deforming is enough to preserve the local properties, global area, boundary curve and relative point location of the shape in the process of deformation. Therefore, some improvements to the deformation algorithm based on non-linear least squares optimizations are carried out, and ineffective constraints are discarded, so the problem is simplified. Sufficient theoretical analysis and experiments proved the advantage of the improved algorithm that first it is more stable, secondly the calculating load is reduced and the computing speed is accelerated.