I am interested in machine learning (ML)-based image classification. Thus, I thought this book may be an interesting read about how ML techniques are applied to fingerprinting. As it turns out, the book is not about ML, but just plain mathematics and algorithms--which is not bad at all. Nevertheless, I found the book helpful, as I had to read a bachelor thesis by one of my students that mentions fingerprinting identification and especially minutiae-based representation and identification methods for smart home systems.

The book starts with a review of the current state of the art in 2D fingerprint identification. It then explains methods, especially those for contactless 3D fingerprint acquisition. The methodology and mathematics are shown in detail via many figures and pictures. The author clearly details how the various processing steps work together, and how cameras and illumination should be used for optimal results. The core of the book (about half) covers the mathematical foundations of fingerprint identification. Pseudocode is used to explain some identification methods.

After reading the book, while I did not follow all of the mathematical details, I could at least understand how it works, what it can be used for, and what are the advantages and the problems. And it gave me some background for the bachelor thesis.

In summary, this is a book for specialists in this area. Mathematics is used and explained; readers can follow along with basic university-level knowledge, but they must invest some time. What I missed--or at least I could not find--are references for implementation and source code for experimentation.