A knowledge model for gray scale image interpretation with emphasis on welding defect classification-An ontology based approach

被引:6
作者
Anouncia, S. Margret [1 ]
Saravanan, R. [1 ]
机构
[1] VIT Univ, Sch Comp Sci, Vellore 632014, Tamil Nadu, India
关键词
Knowledge; Image interpretation; Domain ontology; Image features and gray scale image; RECOGNITION;
D O I
10.1016/j.compind.2010.05.003
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Image interpretation is the process of mapping the content of the image to a real world object that is easily understandable by any user. To perform any image interpretation, the image information is extracted through feature extraction and is then mapped to the known objects of any domain. In order to retain the extracted feature information of the domain for reusability, a proper modeling of the image content is required. This helps in maximizing the leverage of knowledge in image interpretation of specific domain through a computer interpretable model which results as a knowledgebase. This paper focuses on such a modeling for gray scale image interpretation emphasizing on welding defect classification which resulted in domain ontology of welding defects. Domain ontology is created by formalizing the information related to the gray scale image and its significance in welding defects. The developed system is evaluated using industrial radiographs to detect and classify welding defects. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:742 / 749
页数:8
相关论文
共 25 条
[1]   Ontology based process plan generation for image processing [J].
Anouncia, S. Margret ;
Saravanan, R. .
International Journal of Metadata, Semantics and Ontologies, 2007, 2 (03) :211-222
[2]  
BOTTONI P, 1991, ACM SIGAPL, V21
[3]   Borg: A knowledge-based system for automatic generation of image processing programs [J].
Clouard, R ;
Elmoataz, A ;
Porquet, C ;
Revenu, M .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1999, 21 (02) :128-144
[4]   Pattern recognition of weld defects detected by radiographic test [J].
da Silva, RR ;
Calôba, LP ;
Siqueira, MHS ;
Rebello, JMA .
NDT & E INTERNATIONAL, 2004, 37 (06) :461-470
[5]  
Feher Z., 2000, Periodica Polytechnica Electrical Engineering, V44, P241
[6]  
Ficet-Cauchard V, 1998, LECT NOTES ARTIF INT, V1488, P437, DOI 10.1007/BFb0056354
[7]   Intelligent systems in the automotive industry: applications and trends [J].
Gusikhin, Oleg ;
Rychtyckyj, Nestor ;
Filev, Dimitar .
KNOWLEDGE AND INFORMATION SYSTEMS, 2007, 12 (02) :147-168
[8]  
Hamada T, 2000, INT C PATT RECOG, P430, DOI 10.1109/ICPR.2000.906104
[9]   Fuzzy spatial relation ontology for image interpretation [J].
Hudelot, Celine ;
Atif, Jamal ;
Bloch, Isabelle .
FUZZY SETS AND SYSTEMS, 2008, 159 (15) :1929-1951
[10]  
LAWSON SW, 1994, P SOC PHOTO-OPT INS, V2347, P245, DOI 10.1117/12.188736