Intelligent Image Analysis for Plant Phenotyping reviews information on time-saving techniques for identifying plant traits using computer vision and imaging technologies. Beautifully illustrated with numerous color images, this book is written for those working at the intersection of computer vision and plant sciences.

PART I Basics Chapter 1 Image-Based Plant Phenotyping: Opportunities and Challenges Chapter 2 Multisensor Phenotyping for Crop Physiology Chapter 3 Image Processing Techniques for Plant Phenotyping PART II Techniques Chapter 4 Segmentation Techniques and Challenges in Plant Phenotyping Chapter 5 Structural High-Throughput Plant Phenotyping Based on Image Sequence Analysis Chapter 6 Geometry Reconstruction of Plants Chapter 7 Image-Based Structural Phenotyping of Stems and Branches Chapter 8 Time Series- and Eigenvalue-Based Analysis of Plant Phenotypes Chapter 9 Data-Driven Techniques for Plant Phenotyping Using Hyperspectral Imagery Chapter 10 Machine Learning and Statistical Approaches for Plant Phenotyping Chapter 11 A Brief Introduction to Machine Learning and Deep Learning for Computer Vision PART III Practice Chapter 12 Chlorophyll a Fluorescence Analyses to Investigate the Impacts of Genotype, Species, and Stress on Photosynthetic Efficiency and Plant Productivity Chapter 13 Predicting Yield by Modeling Interactions between Canopy Coverage Image Data, Genotypic and Environmental Information for Soybeans Chapter 14 Field Phenotyping for Salt Tolerance and Imaging Techniques for Crop Stress Biology Chapter 15 The Adoption of Automated Phenotyping by Plant Breeders