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The Development of Efficient Multimedia Retrieval System of the Object-Based using the Hippocampal Neural Network  

Jeong Seok-Hoon (Dept. of Electronics, Dong-A University)
Kang Dae-Seong (Dept. of Electronics, Dong-A University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.43, no.2, 2006 , pp. 57-64 More about this Journal
Abstract
Tn this paper, We propose a user friendly object-based multimedia retrieval system using the HCNN(HippoCampus Neural Network. Most existing approaches to content-based retrieval rely on query by example or user based low-level features such as color, shape, texture. In this paper we perform a scene change detection and key frame extraction for the compressed video stream that is video compression standard such as MPEG. We propose a method for automatic color object extraction and ACE(Adaptive Circular filter and Edge) of content-based multimedia retrieval system. And we compose multimedia retrieval system after learned by the HCNN such extracted features. Proposed HCNN makes an adaptive real-time content-based multimedia retrieval system using excitatory teaming method that forwards important features to long-term memories and inhibitory learning method that forwards unimportant features to short-term memories controlled by impression.
Keywords
MPEG; Neural Network; Content-based Retrieval; Object Extraction;
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