Associative memory model for searching an image database by image snippet

Javed I. Khan; David Y. Yun

doi:10.1117/12.186002

16 September 1994 Associative memory model for searching an image database by image snippet

Javed I. Khan, David Y. Yun

Proceedings Volume 2308, Visual Communications and Image Processing '94; (1994) https://doi.org/10.1117/12.186002
Event: Visual Communications and Image Processing '94, 1994, Chicago, IL, United States

Abstract

This paper presents an associative memory called an multidimensional holographic associative computing (MHAC), which can be potentially used to perform feature based image database query using image snippet. MHAC has the unique capability to selectively focus on specific segments of a query frame during associative retrieval. As a result, this model can perform search on the basis of featural significance described by a subset of the snippet pixels. This capability is critical for visual query in image database because quite often the cognitive index features in the snippet are statistically weak. Unlike, the conventional artificial associative memories, MHAC uses a two level representation and incorporates additional meta-knowledge about the reliability status of segments of information it receives and forwards. In this paper we present the analysis of focus characteristics of MHAC.

Citation Download Citation

Javed I. Khan and David Y. Yun "Associative memory model for searching an image database by image snippet", Proc. SPIE 2308, Visual Communications and Image Processing '94, (16 September 1994); https://doi.org/10.1117/12.186002

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