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

Abstract

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.