Content-Based Image Classification

Content-Based Image Classification: Efficient Machine Learning Using Robust Feature Extraction Techniques is a comprehensive guide to research with invaluable image data. Social Science Research Network has revealed that 65% of people are visual learners. Research data provided by Hyerle (2000) has clearly shown 90% of information in the human brain is visual. Thus, it is no wonder that visual information processing in the brain is 60,000 times faster than text-based information (3M Corporation, 2001). Recently, we have witnessed a significant surge in conversing with images due to the popularity of social networking platforms. The other reason for embracing usage of image data is the mass availability of high-resolution cellphone cameras. Wide usage of image data in diversified application areas including medical science, media, sports, remote sensing, and so on, has spurred the need for further research in optimizing archival, maintenance, and retrieval of appropriate image content to leverage data-driven decision-making. This book demonstrates several techniques of image processing to represent image data in a desired format for information identification. It discusses the application of machine learning and deep learning for identifying and categorizing appropriate image data helpful in designing automated decision support systems.

1. Introduction to Content Based Image Classification. 2. A Review of Hand-crafted Feature Extraction Techniques for Content Based Image Classification. 3. Content Based Feature Extraction: Color Averaging. 4. Content Based Feature Extraction: Image Binarization. 5. Content Based Feature Extraction: Image Transforms. 6. Content Based Feature Extraction: Morphological Operators. 7. Content Based Feature Extraction: Texture Components. 8. Fusion Based Classification: A Comparison of Early Fusion and Late Fusion Architecture for Content Based Features. 9. Future Directions: A Journey from Handcrafted Techniques to Representation Learning. 10. WEKA: Beginners' Tutorial