A multidisciplinary domain that indirectly supports information technology (IT) and botanic areas--image analysis modeling and the associated algorithms for implementing automatic systems for plant species identification--is addressed in this book.

Five chapters comprise the book, with the goal of making clear “a novel diagnostic method for plant species identification developed from a computer scientist’s perspective.” Historical background and different practical applications are also included. The conclusions underlined at the end of each chapter allow readers to select at a first glance the most important ideas for their own use.

The book starts with general ideas regarding the use of mathematical methods for “analysis and classification of leaves, leading to novel techniques and a framework for a robust, automated plant identification system.”

The next topics focus on a brief review regarding morphometrics. Chapter 3, “Feature Extraction,” proposes a comparative study regarding leaf-shape analysis techniques and different methods “for extraction and description of leaf macro- and micro-texture, margin characters, and venation patterns,” in order to provide descriptors to be used in automated leaf comparison and classification.

Chapter 4 aims to introduce machine learning algorithms for plant leaf analysis, putting into evidence a “probabilistic classification combining multiple leaf feature sets” and “a technique for automatic selection among feature-sets on a leaf-by-leaf basis.”

The final chapter provides a “Botanists’ Vision,” that is, an algorithm that uses a small set of filters in order to discover the fixation points in an image.

The book is very well written, in a clear and well-structured style, and is an excellent recommendation for specialists, experts, and students in the field of computational botany. At the same time, a solid mathematical background is necessary in order to understand the book’s concepts and the algorithms’ applications.