The book presents selected methods for accelerating image retrieval and classification in large
collections of images using what are referred to as 'hand-crafted features.' It introduces
readers to novel rapid image description methods based on local and global features as well as
several techniques for comparing images. Developing content-based image comparison retrieval
and classification methods that simulate human visual perception is an arduous and complex
process. The book's main focus is on the application of these methods in a relational database
context. The methods presented are suitable for both general-type and medical images. Offering
a valuable textbook for upper-level undergraduate or graduate-level courses on computer science
or engineering as well as a guide for computer vision researchers the book focuses on
techniques that work under real-world large-dataset conditions.
