Image Based Approaches for Tunnels' Defects Recognition via Robotic Inspectors

被引：33

作者：

Protopapadakis, Eftychios ^{[1
,3
]}

Doulamis, Nikolaos ^{[2
,3
]}

机构：

[1] Tech Univ Crete, Khania 73100, Greece

[2] Natl Tech Univ Athens, Athens 15780, Greece

[3] Inst Commun & Comp Syst, Athens, Greece

来源：

ADVANCES IN VISUAL COMPUTING, PT I (ISVC 2015) | 2015年 / 9474卷

关键词：

CRACKS; VISION; SYSTEM; MODEL;

D O I：

10.1007/978-3-319-27857-5_63

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we present a visual based approach, utilized for the detection of concrete defects in tunnels. The detection mechanism is a hybrid approach, based on both image processing and deep learning models. Initial detections are validated by an expert, in order to create a robust data set in short time, saving resources during annotation process. Then, a deep-learning classifier is trained and applied for the inspection. The fully automated system, performs well, in various environments, and can be, easily, implemented with most robotic systems.

引用

页码：706 / 716

页数：11

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