Open AccessRECOGNITION OF PATTERNS ON FRACTURE SURFACES BY AUTOMATIC IMAGE ANALYSIS
Author(s) -
Jacek Komenda,
Maroli Barbara,
Höglund Lars
Publication year - 2011
Publication title -
image analysis and stereology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.237
H-Index - 27
eISSN - 1854-5165
pISSN - 1580-3139
DOI - 10.5566/ias.v21.p207-213
Subject(s) - fracture (geology) , artificial intelligence , classifier (uml) , porosity , image (mathematics) , software , measure (data warehouse) , computer science , pattern recognition (psychology) , computer vision , materials science , composite material , data mining , programming language
Image Classifier, the software package integrated with the MicroGOP2000/S system (Sweden), is applied to quantitatively analyse fracture surfaces. After training the system in automatic recognition of different fracture morphologies, measurements of apparent porosity in three sintered steel specimens are performed The results are related to the bending fatigue limits. Automatic recognition is also used to measure the coarseness of fracture surfaces related to the so-called Jernkontoret Fracture Standard Set Number