Applying GA for Optimizing the User Query in Image and Video Retrieval
In information retrieval systems, queries may be based on user sketches. The new method presented here, optimizes the user sketch before implementation. This optimization may be used in Content-Based Image Retrieval (CBIR) and Content-Based Video Retrieval (CBVR) which is based on trajectory extract...
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| Format: | Article |
| Langue: | English |
| Publié: |
OICC Press
2024-02-01
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| Collection: | Majlesi Journal of Electrical Engineering |
| Sujets: | |
| Accès en ligne: | https://oiccpress.com/mjee/article/view/5263 |
| Résumé: | In information retrieval systems, queries may be based on user sketches. The new method presented here, optimizes the user sketch before implementation. This optimization may be used in Content-Based Image Retrieval (CBIR) and Content-Based Video Retrieval (CBVR) which is based on trajectory extraction. To optimize the retrieval process, one stage of retrieval is performed by the user sketch. The retrieval criterion is based on the proposed distance metric from the user query. Retrieved answers are considered as the primary population for evolutionary optimization. The optimized query may be achieved through reproducing and minimizing the proposed measurement by using Genetic algorithm (GA). The optimized query could then be used for the retrieval of concepts from a given Data Base (DB). The proposed algorithms are evaluated for trajectory retrieval from urban traffic surveillance video and image retrieval from a DB. Practical implementations have demonstrated the high efficiency of this system in trajectory retrieval and image indexing.بتÙدÛÙ
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| ISSN: | 2345-377X 2345-3796 |