<abstract xmlns="http://www.w3.org/1999/xhtml"><p> This work extends the dynamic programming approach to calculation of an elastic metric between two curves to finding paths in pairs of graph drawings that are closest under this metric. The new algorithm effectively solves this problem when all paths between two given nodes in one of these graphs have the same length. It is then applied to the problem of pattern recognition constrained by a superpixel segmentation. Segmentations of test images, obtained without statistical modeling given two shape endpoints, have good accuracy.</p></abstract>

This work extends the dynamic programming approach to calculation of an elastic metric between two curves to finding paths in pairs of graph drawings that are closest under this metric. The new algorithm effectively solves this problem when all paths between two given nodes in one of these graphs have the same length. It is then applied to the problem of pattern recognition constrained by a superpixel segmentation. Segmentations of test images, obtained without statistical modeling given two shape endpoints, have good accuracy.

Closest Paths in Graph Drawings under an Elastic Metric

International Journal of Applied Mathematics and Computer Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Closest Paths in Graph Drawings under an Elastic Metric"}

This work extends the dynamic programming approach to calculation of an elastic metric between two curves to finding paths in pairs of graph drawings that are...

Closest Paths in Graph Drawings under an Elastic Metric

Publicado en línea: 29 jun 2018

Páginas: 387 - 397

Recibido: 15 may 2017

Aceptado: 19 nov 2017

DOI: https://doi.org/10.2478/amcs-2018-0029

Palabras clave
elastic shape analysis, pattern recognition, superpixel segmentation

© 2018 Mateusz Baran, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Closest Paths in Graph Drawings under an Elastic Metric

Publicado en línea: 29 jun 2018

Páginas: 387 - 397

Recibido: 15 may 2017

Aceptado: 19 nov 2017

DOI: https://doi.org/10.2478/amcs-2018-0029

Palabras claveelastic shape analysis, pattern recognition, superpixel segmentation

© 2018 Mateusz Baran, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Palabras clave
elastic shape analysis, pattern recognition, superpixel segmentation