Informatica

As musculoskeletal illnesses continue to increase, practical computerised muscle modelling is crucial. This paper addresses this concern by proposing a mathematical model for a dynamic 3D geometrical surface representation of muscles using a Radial Basis Function (RBF) approximation technique. The objective is to obtain a smoother surface while minimising data use, contrasting it from classical polygonal (e.g. triangular) surface mesh models or volumetric (e.g. tetrahedral) mesh models. The paper uses RBF implicit surface description to describe static surface generation and dynamic surface deformations based on its spatial curvature preservation during the deformation. The novel method is tested on multiple data sets, and the experiments show promising results according to the introduced metrics.

This paper considers a new method for reconstructing deliberately-corrupted pixels in raster images. Firstly, a faster approach for reconstructing corrupted pixels is proposed by applying a processing-circle instead of a processing-square. It is shown that the obtained quality of the reconstructed image is no worse because of this. The quality of the reconstruction is further improved by controlling the pixel corrupting process within the input image. It is shown that a combination of the processing-circle approach and data-dependent corruption reduces the reconstruction time, and the mistakes of the reconstructed pixels.