CVJul 25, 2015

Thinning Algorithm Using Hypergraph Based Morphological Operators

arXiv:1507.07096v16 citations
Originality Synthesis-oriented
AI Analysis

This work addresses a domain-specific issue in image processing for thinning algorithms, but it appears incremental as it applies an existing hypergraph method to morphological operators.

The paper tackles the problem of errors and irregularities in skeletonization for object recognition by proposing morphological operators based on hypergraphs, which act as filters to remove noise and errors in images.

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.

Foundations

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