A content based image retrieval system based on the fuzzy ARTMAP architecture

ABSTRACT

This study deals with designing a flexible feature space for Content Based Image retrieval Systems (CBIR). For this purpose, initially, a large variety of features are extracted from the regions of the pre-segmented images. Then, the feature set of each object class is learned using the Fuzzy Art Map Architecture, by identifying the weights of each feature for each object class.

In the querying phase, trained set of feature weights are used to find the label of each object class. This task is achieved by combining the regions in the images and computing the maximum membership value for the compound regions, which correspond to a possible object class.

REFERENCES

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Search process

General Terms:
Algorithms, Design, Experimentation

Keywords:
CBIR, fuzzy ARTMAP, region-based object retrieval