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. Language: English