文章基本信息

标题：A REVIEW ON ONTOLOGY-BASED LABEL EXTRACTION FROM IMAGE DATA
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作者：AHMAD ADEL ABU-SHAREHA ; MANDAVA RAJESWARI
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2015
卷号：71
期号：2
出版社：Journal of Theoretical and Applied
摘要：Ontology-based label extraction is extensively used to interpret the semantics found in image and video data. Particularly, ontology-based label extraction is one of the main steps in object class recognition, image annotation, and image disambiguation. These applications have important roles in the field of image analysis, and as such, a number of variations of the ontology-based label extraction used in these applications have been reported in the literature. These variations involve ontology development and utilization, and can affect the applicability (e.g., domain- and application-dependency) as well as the accuracy of the output. Unfortunately, the variability aspect of this variation has neither been established nor tracked. Thus, the variations were not configured. A review of the ontology-based label extraction based on the input data, the utilized technique, and the type of utilized ontology is presented in this paper. The ontology-based label extraction is categorized based on two aspects, namely, the type of input data and the type of ontology used. These two aspects determine the type of the label extraction technique to be used. As a result, the relative advantages and disadvantages of each category are determined. The gaps and future research directions in this field are also highlighted.
关键词：Label Extraction; Ontology; Semantics; Semantic Tagging; Knowledge Markup; Image Object Recognition; Image Disambiguation; Image Annotation