Authors:
Yannick Faula
;
Stéphane Bres
and
Véronique Eglin
Affiliation:
Université de Lyon, France
Keyword(s):
Line Detection, Crack Detection, Feature Extraction.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Image and Video Analysis
;
Segmentation and Grouping
Abstract:
Key structures extraction like points, short-lines or regions extraction is a big issue in computer vision. Many
fields of application need large image acquisition and fast extraction of fine structures. Several methods have
been proposed with different accuracies and execution times. In this study, we focus on situations where existing
local feature extractors give not enough satisfying results concerning both accuracy and time processing.
Especially, we focus on short-line extraction in local low-contrasted images. To this end, we propose a new
Fast Local Analysis by threSHolding (FLASH) designed to process large images under hard time constraints.
We apply FLASH on the field of concrete infrastructure monitoring where robots and UAVs(Unmanned Aerial
Vehicles) are more and more used for automated defect detection (like cracks). For large concrete surfaces,
there are several hard constraints such as the computational time and the reliability. Results show that the
computati
ons are faster than several existing algorithms without learning stage, and lead to an automated
monitoring of infrastructures.
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