Computational Botany discusses innovative methods for mining information from images of plants, especially leaves, and highlights the diagnostic features that can be implemented in fully automatic systems for identifying plant species. Adopting a multidisciplinary approach, it explores the problem of plant species identification, covering concepts in both taxonomy and morphology. An overview of morphometrics includes historical background and the main steps in the morphometric analysis of leaves together with a number of applications. The core of Computational Botany focuses on novel diagnostic methods for plant species identification developed from the perspective of a computer scientist. It concludes with a chapter on the characterization of botanists' vision, highlighting important cognitive aspects that can be implemented in a computer system so as to replicate more accurately the human expert's fixation process. Computational Botany not only represents an authoritative guide to advanced computational tools for plant identification, but offers new ideas and challenges to experts in botany, computer science and pattern recognition. It should help to foster closer collaboration and further technological developments in the emerging field of automatic plant identification.
- From the Content
- Introduction
- Morphometrics: a Brief Review
- Feature Extraction
- Machine Learning for Plant Leaf Analysis