Classical methods, including sparse representation classification (SRC) and neural
networks (NNs), classify image object (s) using features like intensity, color, texture, and …

We propose a novel skeleton-based approach to gait recognition using our Skeleton
Variance Image. The core of our approach consists of employing the screened Poisson …

Hierarchies, such as the tree of shapes, are popular representations for image simplification
and segmentation thanks to their multiscale structures. Selecting meaningful level lines …

The objects' features play significant role in the machine learning classification. The present
paper proofs and validates that the shapes of vector field (VF) singular points (SPs) …

This paper develops a new active contour (AC) model capable of multiple complex objects
segmentation in the presence of heavy noise. The model segments images in the framework …

The main objective of this paper is to present a repository of image databases whose
features are augmented with embedded vector field (VF) features. The repository is …

Classification methods use image object features to distinguish between objects and assign
them to classes. In the present study we develop a convolutional neural network (CNN) …

In this paper we solve the Poisson partial differential equation (PDE) with a free right side,
which is a function of the image and its gradient. We call such a PDE Poisson Image (PI) …

Shape abstraction is an important problem faced by researchers in many fields such as
pattern recognition, computer vision, and industrial design. A recently-developed previous …

Disk shape frequently appears as a reference in shape characterization applications. We
propose a local measure of deviation from a disk as the local difference between numerical …