Computational Botany: Methods for Automated Species Identification by Remagnino, Paolo/ Cope, James/ Wilkin, Paul/ Kirkup, Donald William/ Mayo, Simon Joseph: Brand New Hardcover (2016)

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124 pages. 9.75x6.25x0.50 inches. In Stock.

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Bibliographic Details

Title: Computational Botany: Methods for Automated Species Identification
Publisher: Springer-Verlag New York Inc
Publication Date: 2016
Language: English
ISBN 10: 3662537435
ISBN 13: 9783662537435
Binding: Hardcover
Condition: Brand New

About this title

Synopsis

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.

From the Back Cover

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.

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