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Generating Strictly Controlled Stimuli for Figure Recognition Experiments
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Iconic indexing by 2-d strings.

S K Chang1, Q Y Shi, C W Yan

  • 1Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL 60616; Department of Computer Science, University of Pittsburgh, Pittsburgh, PA 152.

IEEE Transactions on Pattern Analysis and Machine Intelligence
|April 21, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method for representing symbolic pictures using two-dimensional (2-D) strings, enabling efficient pictorial information retrieval through 2-D subsequence matching.

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Area of Science:

  • Computer Science
  • Information Retrieval
  • Image Processing

Background:

  • Traditional methods for pictorial information retrieval often face challenges with scalability and efficiency.
  • Representing complex visual data in a searchable format is crucial for large image databases.

Purpose of the Study:

  • To develop a new representation for symbolic pictures using two-dimensional (2-D) strings.
  • To establish a framework for pictorial information retrieval based on 2-D string matching.
  • To analyze the properties of 2-D string representations for image indexing.

Main Methods:

  • Encoding symbolic pictures into their unique 2-D string representations.
  • Developing algorithms for reconstructing pictures from their 2-D string format.
  • Implementing 2-D subsequence matching algorithms for query processing.
  • Proving conditions for characterizing ambiguous pictures in 2-D string formats.

Main Results:

  • A novel 2-D string representation for symbolic pictures has been successfully developed.
  • Efficient algorithms for encoding, reconstruction, and matching of 2-D strings are presented.
  • The approach facilitates direct pictorial information retrieval via 2-D subsequence matching.

Conclusions:

  • The proposed 2-D string representation offers an efficient and natural method for constructing iconic indexes.
  • This technique enhances the capabilities of pictorial information retrieval systems.
  • The mathematical characterization of ambiguous pictures provides theoretical underpinnings for the method.