Artificial Intelligence for Maximizing Content Based Image Retrieval, 1st Edition

  • Published By:
  • ISBN-10: 1605661759
  • ISBN-13: 9781605661759
  • Grade Level Range: College Freshman - College Senior
  • 430 Pages | eBook
  • Original Copyright 2008 | Published/Released July 2009
  • This publication's content originally published in print form: 2008

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Discusses major aspects of content-based image retrieval (CBIR) using current technologies and applications within the artificial intelligence (AI) field.

Table of Contents

Front Cover.
Title Page.
Copyright Page.
Table of Contents.
Detailed Table of Contents.
1: I.
2: Genetic Algorithms and Other Approaches in Image Feature Extraction and Representation.
3: Improving Image Retrieval by Clustering.
4: Review on Texture Feature Extraction and Description Methods in Content-Based Medical Image Retrieval.
5: Content-Based Image Classification and Retrieval: A Rule-Based System Using Rough Sets Framework.
6: II.
7: Content Based Image Retrieval Using Active-Nets.
8: Content-Based Image Retrieval: From the Object Detection/Recognition Point of View.
9: Making Image Retrieval and Classification More Accurate Using Time Series and Learned Constraints.
10: A Machine Learning-Based Model for Content-Based Image Retrieval.
11: III.
12: Solving the Small and Asymmetric Sampling Problem in the Context of Image Retrieval.
13: Content Analysis from User's Relevance Feedback for Content–Based Image Retrieval.
14: Preference Extraction in Image Retrieval.
15: Personalized Content-Based Image Retrieval.
16: IV.
17: A Semantics Sensitive Framework of Organization and Retrieval for Multimedia Databases.
18: Content-Based Retrieval for Mammograms.
19: Event Detection, Query, and Retrieval for Video Surveillance.
20: MMIR: An Advanced Content–Based Image Retrieval System Using a Hierarchical Learning Framework.
21: Compilation of References.
About the Contributors.