Examination of root development by means of topological image analysis (bibtex)

by Ines Janusch

Abstract:

The focus of this work is to examine root plant development by means of topological image analysis. As roots grow and develop they change their shape (for example when branches are formed). Due to this aspect this application is well suited for a topological analysis. The aim of the scientific practical is to represent the root images as Reeb graphs. A method to compute critical points using a height function and to build a Reeb graph based on these points, is presented. All nodes in the graph are classified according to their type and their color. There are four different types of nodes in a Reeb graph: minima, maxima, saddle nodes and regular nodes. When storing color information with the nodes and interpret the graylevels as levels of elevation, the nodes can be further classified according to their elevation.

Reference:

Examination of root development by means of topological image analysis (Ines Janusch), Technical report, PRIP, TU Wien, 2013.

Bibtex Entry:

@TechReport{TR131, author = "Ines Janusch", title = "Examination of root development by means of topological image analysis", institution = "PRIP, TU Wien", number = "PRIP-TR-131", year = "2013", url = "ftp://ftp.prip.tuwien.ac.at/pub/publications/trs/tr131.pdf", abstract = "The focus of this work is to examine root plant development by means of topological image analysis. As roots grow and develop they change their shape (for example when branches are formed). Due to this aspect this application is well suited for a topological analysis. The aim of the scientific practical is to represent the root images as Reeb graphs. A method to compute critical points using a height function and to build a Reeb graph based on these points, is presented. All nodes in the graph are classified according to their type and their color. There are four different types of nodes in a Reeb graph: minima, maxima, saddle nodes and regular nodes. When storing color information with the nodes and interpret the graylevels as levels of elevation, the nodes can be further classified according to their elevation.", }

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