Semantic-Based Image Retrieval Using Balanced Clustering Tree
| Autor: | Nguyen Thi Uyen Nhi, Thanh The Van, Thanh Manh Le |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Computer science
business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020206 networking & telecommunications Pattern recognition 02 engineering and technology computer.file_format Ontology (information science) Semantics Image (mathematics) Set (abstract data type) Tree (data structure) 0202 electrical engineering electronic engineering information engineering SPARQL 020201 artificial intelligence & image processing Artificial intelligence business Cluster analysis computer Image retrieval |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783030726508 WorldCIST (2) |
| Popis: | In this paper, we propose a model for semantic-based image retrieval (SBIR) on the clustering balanced tree, C-Tree, and ontology to analyze the semantics of an image and extract a similar set of images, in which the input is a query image. This structure is constructed rely on separating the nodes from the leaf node and growing towards the root to create a balanced tree. A set of similar images are searched on the C-Tree to classify the query image based on the k-NN (k-Nearest Neighbor) algorithm. Then, the SPARQL query is generated to query the semantics of the image on ontology. We experimented with image datasets such as COREL (1000 images), Wang (10,800 images), ImageCLEF (20,000 images). The results are compared and evaluated with the relevant projects published recently on the same datasets. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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