Computational Botany: Methods for Automated Species Identification

ISBN-13: 9783662537435 / Angielski / Twarda / 2016 / 114 str.

Paolo Remagnino; James Cope; Paul Wilkin

Opis

This book 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.

Recenzje

"This book is a laudable outcome of an interdisciplinary research collaboration. ... it is an important source in the development of highly automated approaches of plant identification. ... an important contribution for students and researchers in plant science as well as computational botanists." (S. Suresh Ramanan and Anatoliy A. Khapugin, Current Science, Vol. 115 (2), July, 2018)

"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. ... 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." (Computing Reviews, September, 2017) 

Spis treści

From the Content.- Introduction.- Morphometrics: a Brief Review.- Feature Extraction.- Machine Learning for Plant Leaf Analysis.

Blurb

This book 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 both the concepts of taxonomy and morphology. It then provides an overview of morphometrics, including the historical background and the main steps in the morphometric analysis of leaves together with a number of applications. The core of the book focuses on novel diagnostic methods for plant species identification developed from a computer scientist’s perspective. It then concludes with a chapter on the characterization of botanists' visions, which highlights important cognitive aspects that can be implemented in a computer system to more accurately replicate the human expert’s fixation process. The book not only represents an authoritative guide to advanced computational tools for plant identification, but provides experts in botany, computer science and pattern recognition with new ideas and challenges. As such it is expected to foster both closer collaborations and further technological developments in the emerging field of automatic plant identification.