CBIR System Based On Prediction Errors


Ahamed Ayoobkhan, Mohamed Uvaze and Ramakrishnan, Kannan and Eswaran, Chikkannan (2017) CBIR System Based On Prediction Errors. Journal of Information Science and Engineering, 33 (2). pp. 347-365. ISSN 1016-2364

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Content-Based Image Retrieval (CBIR) systems are widely used for local as well as for remote applications such as telemedicine, satellite image transmission and image search engines. The existing CBIR systems suffer from the limitations of storage space, data security and bandwidth requirement. To overcome these problems, a new method termed as CBIR-PE which makes use of prediction errors instead of actual images for storage, transmission and retrieval is presented. Identical artificial neural networks (ANNs) are employed both at the server and client sides to carry out the prediction. At the server side, only the error database comprising the difference between the original and the predicted pixel values is used instead of the actual image database. The predic-tion errors of the query image are matched with those in the server database to retrieve similar prediction error patterns. These errors are then combined with the predicted val-ues available at the client ANN to reconstruct the actual images. Since only the predic-tion errors are employed, the proposed method is able to solve the problems of storage space, data security and bandwidth requirement. The proposed method is implemented in combination with a clustering technique called WBCT-FCM which makes use of wavelet based contourlet transform (WBCT) and fuzzy c-means (FCM) clustering algorithm. The performances of the proposed WBCT-FCM and CBIR-PE are evaluated using COREL-1k database. The experimental results show that the proposed methods achieve better results with respect to clustering and retrieval accuracies compared to the existing methods.

Item Type: Article
Uncontrolled Keywords: Content-based image retrieval
Subjects: Z Bibliography. Library Science. Information Resources > ZA3038-5190 Information resources (General) > ZA4050-4775 Information in specific formats or media > ZA4550-4575 Motion pictures. Video recordings
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 20 Jul 2020 03:32
Last Modified: 20 Jul 2020 03:32
URII: http://shdl.mmu.edu.my/id/eprint/6938


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