Retrieval by Shape Population: An Index Tree Approach

Abstract

Based on our previous work in deformable shape model based object detection, a new method is proposed that uses index trees for organizing shape features to support content based retrieval applications. In the proposed strategy, different shape feature sets can be used in index trees constructed for object detection and shape similarity comparison respectively. There is a direct correspondence between the two shape feature sets. As a result, application-specific features can be obtained efficiently for shape-based retrieval after object detection. A novel approach is proposed that allows retrieval of images based on the population distribution of deformed shapes in each image. Experiments testing these new approaches have been conducted using an image database that contains blood cell micrographs. The precision vs. recall performance measure shows that our method is superior to previous methods.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2001
Accession Number
ADA443225

Entities

People

  • Lifeng Liu
  • Stan Sclaroff

Organizations

  • Boston University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Blood
  • Blood Cells
  • Cells
  • Change Detection
  • Clustering
  • Computations
  • Computer Science
  • Computer Vision
  • Computers
  • Databases
  • Demography
  • Detection
  • Image Processing
  • Image Segmentation
  • Precision

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Database Systems and Applications