Invariant representative cocycles of cohomology generators using irregular graph pyramids

Structural pattern recognition describes and classifies data based on the relationships of features and parts. Topological invariants, like the Euler number, characterize the structure of objects of any dimension. Cohomology can provide more refined algebraic invariants to a topological space than d...

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Detalles Bibliográficos
Autores: González Díaz, Rocío, Ion, Adrián, Iglesias Ham, Mabel, Kropatsch, Walter G.
Tipo de recurso: artículo
Fecha de publicación:2011
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/30803
Acceso en línea:http://hdl.handle.net/11441/30803
https://doi.org/doi:10.1016/j.cviu.2010.12.009
Access Level:acceso abierto
Palabra clave:Graph pyramids
Representative cocycles of cohomology generators
Descripción
Sumario:Structural pattern recognition describes and classifies data based on the relationships of features and parts. Topological invariants, like the Euler number, characterize the structure of objects of any dimension. Cohomology can provide more refined algebraic invariants to a topological space than does homology. It assigns ‘quantities’ to the chains used in homology to characterize holes of any dimension. Graph pyramids can be used to describe subdivisions of the same object at multiple levels of detail. This paper presents cohomology in the context of structural pattern recognition and introduces an algorithm to efficiently compute representative cocycles (the basic elements of cohomology) in 2D using a graph pyramid. An extension to obtain scanning and rotation invariant cocycles is given.