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An Incremental Evolutionary Method For Optimizing Dynamic Image Retrieval Systems

Publish Year: 1389
Type: Conference paper
Language: English
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Document National Code:

ICMVIP06_057

Index date: 9 April 2011

An Incremental Evolutionary Method For Optimizing Dynamic Image Retrieval Systems abstract

This paper introduces a new incremental evolutionary optimization method based on evolutionary group algorithm (EGA). The EGA was presented as an approach to overcome time-consuming drawbacks related to general evolutionary algorithms in large scale content-based image indexing retrieval (CBIR) optimization tasks. Here, we consider another challengeable limitation of usual evolutionary learning and optimization systems: learning in the scale-varying and dynamic environments. Hence, we present a new strategy based on EGA that is enhanced with the ability of incremental learning. Evaluation results on scale-varying and simulated dynamic CBIR systems show that the proposed method can continuously obtain good performance in the presence of environmental or scale changes.

An Incremental Evolutionary Method For Optimizing Dynamic Image Retrieval Systems Keywords:

Content-Based Image Indexing and Retrieval , Wavelet Correlogram , Evolutionary Algorithms (EAs) , Incremental Learning

An Incremental Evolutionary Method For Optimizing Dynamic Image Retrieval Systems authors

Mohammad Nikzad

Islamic Azad University Science and Research branch, Tehran

Hamid Abrishami Moghaddam

K.N Toosi University of Technology, Tehran, Iran,