Euclidean Graphs as Crack Pattern Descriptors for Automated Crack Analysis in Digital Images.

ABSTRACT: Typical crack detection processes in digital images produce a binary-segmented image that constitutes the basis for all of the following analyses. Binary images are, however, an unsatisfactory data format for advanced crack analysis algorithms due to their sparse nature and lack of significant data structuring. Therefore, this work instead proposes a new approach based on Euclidean graphs as functional crack pattern descriptors for all post-detection analyses. Conveying both geometrical and topological information in an integrated representation, Euclidean graphs are an ideal structure for efficient crack path description, as they precisely locate the cracks on the original image and capture salient crack skeleton features. Several Euclidean graph-based algorithms for autonomous crack refi

SUBMITTER: Strini A 

PROVIDER: S-EPMC9414651 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature