Document Details

Document Type : Thesis 
Document Title :
Multi Sources Fusion Method for Image Retrieval System
أسلوب دمج المعلومات من مصادر متعددة لأنظمة استرجاع الصور
 
Subject : Faculty of Computing and Information Technology 
Document Language : Arabic 
Abstract : Recently, image retrieval in general and in content-based image retrieval specially became a very important research area used in different fields. From the early days, content-based image retrieval systems suffer from the “semantic gap problem” which is the lack of coincidence between the low level visual features of the image and the high-level human perception. The proposed thesis tries to bridge this gap by designing an image retrieval system for the Web using a multimodal fusion retrieval technique. The proposed retrieving method utilizes the fusion of the images’ multimodal information (textual and visual) which is a recent trend in image retrieval researches. It combines two different data mining techniques to retrieve semantically related images: clustering and association rules mining algorithm. The semantic association rules mining is constructed at the offline phase where the association rules are discovered between the text semantic clusters and the visual clusters of the images to use it later in the online phase. The experiment was conducted on more than 54,500 images of ImageCLEF 2011 Wikipedia collection. It was compared to an online image retrieving system called MMRetrieval and to the proposed system but without using association rules. The obtained results show that the proposed method achieved the best precision score among different query categories 
Supervisor : Dr. Mohammad Abdoulshakoor 
Thesis Type : Master Thesis 
Publishing Year : 1435 AH
2014 AD 
Co-Supervisor : Dr. Mounira Taileb 
Added Date : Monday, July 21, 2014 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
رانية احمد الغامديAlghamdi, Raniah AhmadResearcherMaster 

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