Integrated Region-Based Image Retrieval
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Home > Computing and Information Technology > Databases > Integrated Region-Based Image Retrieval: (11 The Information Retrieval Series)
Integrated Region-Based Image Retrieval: (11 The Information Retrieval Series)

Integrated Region-Based Image Retrieval: (11 The Information Retrieval Series)


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About the Book

The need for efficient content-based image retrieval has increased in areas such as biomedicine, military, commerce, education, and Web image classification and searching. In the biomedical domain, content-based image retrieval can be used in patient digital libraries, clinical diagnosis, searching of 2-D electrophoresis gels, and pathology slides. This title presents a wavelet-based approach for feature extraction, combined with integrated region matching. An image in the database, or a portion of an image, is represented by a set of regions, roughly corresponding to objects, which are characterized by colour, texture, shape, and location. A measure for the overall similarity between images is developed as a region-matching scheme that integrates properties of all the regions in the images. The advantage of using this "soft matching" is that it makes the metric robust to poor segmentation, an important property that previous research has not solved. Integrated Region-Based Image Retrieval demonstrates an experimental image retrieval system called SIMPLIcity (Semantics-sensitive Integrated Matching for Picture LIbraries), This system validates these methods on various image databases, proving that such methods perform much better and much faster than existing ones. The system is exceptionally robust to image alterations such as intensity variation, sharpness variation, intentional distortions, cropping, shifting, and rotation. These features are extremely important to biomedical image databases since visual features in the query image are not exactly the same as the visual features in the images in the database. Integrated Region-Based Image Retrieval is an excellent reference for researchers in the fields of image retrieval, multimedia, computer vision and image processing.

Table of Contents:
1. Introduction.- 1. Text-based image retrieval.- 2. Content-based image retrieval.- 3. Applications of CBIR.- 4. Summary of our work.- 5. Structure of the book.- 6. Summary.- 2. Background.- 1. Introduction.- 2. Content-based image retrieval.- 3. Image semantic classification.- 4. Summary.- 3. Wavelets.- 1. Introduction.- 2. Fourier transform.- 3. Wavelet transform.- 4. Applications of wavelets.- 5. Summary.- 4. Statistical Clustering and Classification.- 1. Introduction.- 2. Artificial intelligence and machine learning.- 3. Statistical clustering.- 4. Statistical classification.- 5. Summary.- 5. Wavelet-Based Image Indexing and Searching.- 1. Introduction.- 2. Preprocessing.- 3. Multiresolution indexing.- 4. The indexing algorithm.- 5. The matching algorithm.- 6. Performance.- 7. Limitations.- 8. Summary.- 6. Semantics-Sensitive Integrated Matching.- 1. Introduction.- 2. Overview.- 3. Image segmentation.- 4. Image classification.- 5. The similarity metric.- 6. System for biomedical image databases.- 7. Clustering for large databases.- 8. Summary.- 7. Image Classification by Image Matching.- 1. Introduction.- 2. Industrial solutions.- 3. Related work in academia.- 4. System for screening objectionable images.- 5. Classifying objectionable websites.- 6. Summary.- 8. Evaluation.- 1. Introduction.- 2. Overview.- 3. Data sets.- 4. Query interfaces.- 5. Characteristics of IRM.- 6. Accuracy.- 7. Robustness.- 8. Speed.- 9. Summary.- 9. Conclusions and Future Work.- 1. Summary.- 2. Limitations.- 3. Areas of future work.- References.


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Product Details
  • ISBN-13: 9780792373506
  • Publisher: Kluwer Academic Publishers
  • Publisher Imprint: Kluwer Academic Publishers
  • Height: 235 mm
  • No of Pages: 178
  • Returnable: Y
  • Width: 155 mm
  • ISBN-10: 0792373502
  • Publisher Date: 31 May 2001
  • Binding: Hardback
  • Language: English
  • Returnable: Y
  • Series Title: 11 The Information Retrieval Series


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