Surface crack detection using Hierarchal Convolutional Neural Network

Davis Bonsu Agyemang, Mohamed Bader-El-Den

Research output: Chapter in Book/Report/Conference proceedingConference contribution

105 Downloads (Pure)

Abstract

Cracks on surface walls may imply that a building possesses problems with its structural integrity. Evaluating these types of defects needs to be accurate to determine the condition of the building. Currently, the evaluation of surface cracks is conducted through visual inspection, resulting in occasions of subjective judgements being made on the classification and severity of the surface crack which poses danger for customers and the environment as it not being analysed objectively. Previous researchers have applied numerous classification methods, but they always stop their research at just being able to classify cracks which would not be fully useful for professionals such as surveyors. We propose building a hybrid web application that can classify the condition of a surface from images using a trained Hierarchal-Convolutional Neural Network (H-CNN) which can also decipher if the image that is being looked is a surface or not. For continuous improvement of the H-CNN’s accuracy, the application will have a feedback mechanism for users to send an email query on incorrectly classified images which will be used to retrain the H-CNN.
Original languageEnglish
Title of host publicationAdvances in Computational Intelligence Systems
Subtitle of host publicationContributions Presented at the 19th UK Workshop on Computational Intelligence, September 4-6, 2019, Portsmouth, UK
EditorsZhaojie Ju, Longzhi Yang, Chenguang Yang, Alexander Gegov, Dalin Zhou
PublisherSpringer
Pages173-186
ISBN (Electronic)978-3-030-29933-0, 2194-5365
ISBN (Print)978-3-030-29932-3
DOIs
Publication statusPublished - Sep 2019
Event19th UK Workshop on Computational Intelligence - Portsmouth, United Kingdom
Duration: 4 Sep 20195 Sep 2019
Conference number: 19
https://www.ukci2019.port.ac.uk/

Publication series

NameAdvances in Intelligent Systems and Computing
PublisherSpringer
Volume1043
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Workshop

Workshop19th UK Workshop on Computational Intelligence
Abbreviated titleUKCI 2019
Country/TerritoryUnited Kingdom
CityPortsmouth
Period4/09/195/09/19
OtherThe UKCI 2019 covers both theory and applications in computational intelligence. The topics of interest include
Fuzzy Systems
Neural Networks
Evolutionary Computation
Evolving Systems
Machine Learning
Data Mining
Cognitive Computing
Intelligent Robotics
Hybrid Methods
Deep Learning
Applications of Computational Intelligence
Internet address

Fingerprint

Dive into the research topics of 'Surface crack detection using Hierarchal Convolutional Neural Network'. Together they form a unique fingerprint.

Cite this