Ultrasonic Image Enhancement to Internal Defect Detection during Material Inspection

Ultrasonic waves are efficiently exploited to detect internal defects such as cracks and occlusions in non-destructive testing (NDT) of materials. In some automated procedures, emitter and receiver probes are displaced step by step and signals are displayed to form images that make diagnosis easier...

Full description

Bibliographic Details
Main Authors: Merazi-Meksen Thouraya, Boudraa Malika, Boudraa Bachir
Format: Article
Language:English
Published: EDP Sciences 2018-01-01
Series:MATEC Web of Conferences
Online Access:https://doi.org/10.1051/matecconf/201820801005
id doaj-1c7a79c73c7942979dde36fc025a443f
record_format Article
spelling doaj-1c7a79c73c7942979dde36fc025a443f2021-02-02T05:19:34ZengEDP SciencesMATEC Web of Conferences2261-236X2018-01-012080100510.1051/matecconf/201820801005matecconf_icmie2018_01005Ultrasonic Image Enhancement to Internal Defect Detection during Material InspectionMerazi-Meksen ThourayaBoudraa MalikaBoudraa BachirUltrasonic waves are efficiently exploited to detect internal defects such as cracks and occlusions in non-destructive testing (NDT) of materials. In some automated procedures, emitter and receiver probes are displaced step by step and signals are displayed to form images that make diagnosis easier to interpret. However, too much images are unnecessarily stored when they correspond to safe zones (without presented defects). In this paper, we propose a method that enhances ultrasonic images quality in order to improve the discrimination between images containing or not a shape regarding a detected defect. The method is based on the adapted histogram equalization technique followed by morphological operations that erase all useless shapes on processed images.https://doi.org/10.1051/matecconf/201820801005
collection DOAJ
language English
format Article
sources DOAJ
author Merazi-Meksen Thouraya
Boudraa Malika
Boudraa Bachir
spellingShingle Merazi-Meksen Thouraya
Boudraa Malika
Boudraa Bachir
Ultrasonic Image Enhancement to Internal Defect Detection during Material Inspection
MATEC Web of Conferences
author_facet Merazi-Meksen Thouraya
Boudraa Malika
Boudraa Bachir
author_sort Merazi-Meksen Thouraya
title Ultrasonic Image Enhancement to Internal Defect Detection during Material Inspection
title_short Ultrasonic Image Enhancement to Internal Defect Detection during Material Inspection
title_full Ultrasonic Image Enhancement to Internal Defect Detection during Material Inspection
title_fullStr Ultrasonic Image Enhancement to Internal Defect Detection during Material Inspection
title_full_unstemmed Ultrasonic Image Enhancement to Internal Defect Detection during Material Inspection
title_sort ultrasonic image enhancement to internal defect detection during material inspection
publisher EDP Sciences
series MATEC Web of Conferences
issn 2261-236X
publishDate 2018-01-01
description Ultrasonic waves are efficiently exploited to detect internal defects such as cracks and occlusions in non-destructive testing (NDT) of materials. In some automated procedures, emitter and receiver probes are displaced step by step and signals are displayed to form images that make diagnosis easier to interpret. However, too much images are unnecessarily stored when they correspond to safe zones (without presented defects). In this paper, we propose a method that enhances ultrasonic images quality in order to improve the discrimination between images containing or not a shape regarding a detected defect. The method is based on the adapted histogram equalization technique followed by morphological operations that erase all useless shapes on processed images.
url https://doi.org/10.1051/matecconf/201820801005
work_keys_str_mv AT merazimeksenthouraya ultrasonicimageenhancementtointernaldefectdetectionduringmaterialinspection
AT boudraamalika ultrasonicimageenhancementtointernaldefectdetectionduringmaterialinspection
AT boudraabachir ultrasonicimageenhancementtointernaldefectdetectionduringmaterialinspection
_version_ 1724303922925928448