Shape description from generalized support functions

Authors:
X. Gual-Arnau;S. Herold-GarcíA;A. Simó
Affiliations:
Departamento de Matemítiques-INIT, Universitat Jaume I, Spain;Departamento de Computación, Universidad de Oriente, Cuba;Departamento de Matemítiques-IMAC, Universitat Jaume I, Spain
Venue:
Pattern Recognition Letters
Year:
2013

Citing 15
Cited 0

Computational geometry: an introduction

Computational geometry: an introduction
Geometric shape recognition of freeform curves and surfaces

Graphical Models and Image Processing
Robust Descriptors of Binary Shapes with Applications

International Journal of Computer Vision
Mathematical Morphology and Its Applications to Image and Signal Processing

Mathematical Morphology and Its Applications to Image and Signal Processing
The Complex Representation of Algebraic Curves and Its Simple Exploitation for Pose Estimation and Invariant Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Matching and Object Recognition Using Shape Contexts

IEEE Transactions on Pattern Analysis and Machine Intelligence
On Using Functions to Describe the Shape

Journal of Mathematical Imaging and Vision
Analysis of Planar Shapes Using Geodesic Paths on Shape Spaces

IEEE Transactions on Pattern Analysis and Machine Intelligence
Resuming Shapes with Applications

Journal of Mathematical Imaging and Vision
Shape Estimation from Support and Diameter Functions

Journal of Mathematical Imaging and Vision
Shape Classification Using the Inner-Distance

IEEE Transactions on Pattern Analysis and Machine Intelligence
Fourier Descriptors for Plane Closed Curves

IEEE Transactions on Computers
Functional data analysis in shape analysis

Computational Statistics & Data Analysis
Nearest neighbor pattern classification

IEEE Transactions on Information Theory
Affinity Learning with Diffusion on Tensor Product Graph

IEEE Transactions on Pattern Analysis and Machine Intelligence

Quantified Score

Hi-index	0.10

Visualization

Abstract

The generalized support function is considered to be a representation of shape properties of compact connected sets in R^2. Some interesting properties are studied and several parameters are defined for use in shape description and classification. When these parameters are applied to describe convex figures, they are closely related with the measure of congruent segments of fixed length within the convex figure. Finally, an experimental study is conducted to show the goodness obtained when using the generalized support function in shape classification.