Mining Multimedia Documents

9.4.2.1 Moment Invariants -- 9.4.2.2 Curvature Scale Space -- 9.4.2.3 Beam Angle Statistics -- 9.4.2.4 Tensor Scale Descriptor -- 9.4.2.5 Contour Salience -- 9.4.2.6 Segment Salience -- 9.4.2.7 Distance Transforms -- 9.4.3 Texture-Based Image Retrieval -- 9.4.3.1 Space-Based Approaches -- 9.4.3.2 Frequency-Based Texture Descriptors -- 9.4.3.3 Texture Signatures -- 9.4.4 Clustering-Based Image Retrieval -- 9.4.4.1 Relevance Feedback -- 9.4.4.2 Log-Based Clustering -- 9.4.4.3 Hierarchical Clustering -- 9.4.4.4 Retrieval Dictionary-Based Clustering -- 9.4.4.5 N-Cut Algorithm -- 9.4.4.6 K-Means Clustering -- 9.4.4.7 Graph Theory-Based Clustering -- 9.4.4.8 Divide and Conquer K-Means -- 9.5 Comparative Study -- 9.6 Conclusion -- References -- 10. Knowledge Mining from Medical Images -- 10.1 Introduction -- 10.2 Knowledge Discovery in Databases -- 10.3 Medical Image Mining Techniques in the KDD System -- 10.4 Searching in Medical Image Databases -- 10.5 Applications on Knowledge Discovery in Medical Databases -- 10.6 Applications, Challenges, and Future Aspects -- 10.7 Conclusions -- References -- 11. Segmentation for Medical Image Mining -- 11.1 Introduction -- 11.2 Medical Image Mining for Computer-Aided Diagnosis -- 11.3 Segmentation Algorithms -- 11.4 Machine Learning-Based Segmentation for Medical Image Mining -- 11.5 Segmentation-Based Medical Image Mining Applications -- 11.6 Challenges and Future Perspectives -- 11.7 Conclusion -- References -- 12. Biological Data Mining: Techniques and Applications -- 12.1 Introduction -- 12.2 Bioinformatics Using Data Mining Techniques -- 12.3 Data Mining Techniques -- 12.4 Data Mining for Biological Sequences -- 12.5 Biological Data Mining Applications -- 12.6 Evolution, Challenges, and Future Scope -- 12.7 Conclusion -- References -- 13. Video Text Extraction and Mining -- 13.1 Introduction -- 13.2 Video Mining