A semantics and image retrieval system for hierarchical image databases |
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| Institution: | 1. PDPM Indian Institute of Information Technology, Design and Manufacturing Jabalpur, Dumna Airport Road, Jabalpur 482005 Madhya Pradesh, India;2. Graduate School of Information Science and Engineering, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8552, Japan;1. Institute of Computing, Federal University of Amazonas –Av. Gen. Rodrigo Otávio, 3000, Manaus 69077-000, AM, Brazil;2. Neemu S/A, Av. Via Lactea, 1374, Manaus 69060-020, AM, Brazil;1. Pattern Recognition and Human Language Technology (PRHLT) Research Center, Universitat Politècnica de València, Camino de Vera s/n, Valencia 46022, Spain;2. Computer Science Department, Instituto Nacional de Astrofísica, Óptica y Electrónica, Luis Enrique Erro 1, Puebla 72840, Mexico;1. Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Alicante, Spain;2. Departamento de Computación, Universidad Agraria de La Habana, La Habana, Cuba |
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| Abstract: | This work presents a content based semantics and image retrieval system for semantically categorized hierarchical image databases. Each module is designed with an aim to develop a system that works closer to human perception. Images are mapped to a multidimensional feature space, where images belonging a semantic are clustered and indexed to acquire its efficient representation. This helps in handling the existing variability or heterogeneity within this semantic. Adaptive combinations of the obtained depictions are utilized by the branch selection and pruning algorithms to identify some closer semantics and select only a part of the large hierarchical search space for actual search. So obtained search space is finally used to retrieve desired semantics and similar images corresponding to them. The system is evaluated in terms of accuracy of the retrieved semantics and precision-recall curves. Experiments show promising semantics and image retrieval results on hierarchical image databases. The results reported with non-hierarchical but categorized image databases further prove the efficacy of the proposed system. |
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