Efficient Semantic Video Data Content Extraction Using Fuzzy Ontology


  • Rajeswary A PG, M.Tech. (Department of CSE), Bharathiyar College of Engineering and Technology Thiruvettakudy, Kariakal-609609
  • Gunalan V Assistant Professor, Dept of CSE, Bharathiyar College of Engineering and Technology Thiruvettakudy, Kariakal-609609


ontology, modelling, video semantic


The use of video-based applications has revealed the need for extracting the content in videos. Currently manual techniques which are inefficient subjective and costly in time and limit the querying capabilities are being used to bridge the gap between low-level representative features and high-level semantic content. Here we propose a semantic content extraction system that allows the user to query and retrieve objects, events, and concepts that are extracted automatically. We introduce an ontology-based fuzzy video semantic content model that uses spatial/temporal relations in event and concept definitions. In addition to domain ontology we use additional rule definitions (without using ontology). The proposed framework has been fully implemented and tested on three different domains. We have obtained satisfactory precision and recall rates for object, event and concept extraction.


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How to Cite

Rajeswary, A., & Gunalan, V. (2024). Efficient Semantic Video Data Content Extraction Using Fuzzy Ontology. COMPUSOFT: An International Journal of Advanced Computer Technology, 3(11), 1300–1305. Retrieved from https://ijact.in/index.php/j/article/view/226



Original Research Article

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