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Color image retrieval based on hidden Markov models.

H C Lin1, L L Wang, S N Yang

  • 1Dept. of Comput. Sci., Nat. Tsing Hua Univ., Hsinchu.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1997
PubMed
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This study introduces a novel image retrieval method using two-dimensional pseudo-hidden Markov models (2-D PHMMs) to analyze image content. The approach effectively matches user-painted queries against database images represented by these models.

Area of Science:

  • Computer Science
  • Information Retrieval
  • Image Processing

Background:

  • Traditional image retrieval methods often struggle with capturing complex spatial and chromatic information.
  • Developing efficient and accurate content-based image retrieval (CBIR) systems remains a significant challenge.

Purpose of the Study:

  • To propose a new approach for retrieving images from a color image database.
  • To represent images using a model that captures both chromatic and spatial characteristics.
  • To enable flexible pictorial querying for enhanced user interaction.

Main Methods:

  • Each image in the database is represented by a two-dimensional pseudo-hidden Markov model (2-D PHMM).
  • A flexible pictorial querying method allows users to sketch desired image content.

Related Experiment Videos

  • Image matching is performed by comparing the query sketch against the 2-D PHMMs of database images.

    • Main Results:

    • The proposed 2-D PHMM-based image representation effectively characterizes chromatic and spatial information.
    • The pictorial querying method provides a flexible and intuitive way to search for images.
    • Experimental results demonstrate the effectiveness of the proposed image retrieval approach.

    Conclusions:

    • The 2-D PHMM is a suitable model for representing color images in retrieval systems.
    • The integration of pictorial querying with 2-D PHMMs offers a powerful solution for content-based image retrieval.
    • This approach shows significant promise for improving the accuracy and usability of image databases.