Thinning Algorithm Using Hypergraph Based Morphological Operators

TL;DR

This paper introduces a novel hypergraph-based morphological thinning algorithm that enhances object recognition by reducing noise and irregularities in images, improving skeleton accuracy in shape analysis.

Contribution

It presents a new approach using hypergraph morphological operators for thinning, which prevents errors and irregularities in skeletonization, advancing shape-based image processing techniques.

Findings

Reduces noise and errors in image skeletons

Improves accuracy of line object recognition

Introduces hypergraph-based morphological operators

Abstract

The object recognition is a complex problem in the image processing. Mathematical morphology is Shape oriented operations, that simplify image data, preserving their essential shape characteristics and eliminating irrelevancies. This paper briefly describes morphological operators using hypergraph and its applications for thinning algorithms. The morphological operators using hypergraph method is used to preventing errors and irregularities in skeleton, and is an important step recognizing line objects. The morphological operators using hypergraph such as dilation, erosion, opening, closing is a novel approach in image processing and it act as a filter remove the noise and errors in the images.