• International Journal of Computer Science & Network Security
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• v.24 no.10
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• pp.197-205
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• 2024

This paper introduces a new approach to semantic image retrieval using shape descriptors as dispersion and moment in conjunction with discriminative model of Latent-dynamic Conditional Random Fields (LDCRFs). The target region is firstly localized via the background subtraction model. Then the features of dispersion and moments are employed to k-mean procedure to extract object's feature as second stage. After that, the learning process is carried out by LDCRFs. Finally, SPARQL language on input text or image query is to retrieve semantic image based on sequential processes of Query Engine, Matching Module and Ontology Manger. Experimental findings show that our approach can be successful retrieve images against the mammals Benchmark with rate 98.11. Such outcomes are likely to compare very positively with those accessible in the literature from other researchers.