Computational Botany: Methods for Automated Species Identification

Remagnino, Paolo and Mayo, Simon and Wilkin, Paul and Cope, James and Kirkup, Don (2017) Computational Botany: Methods for Automated Species Identification. Springer Nature, Germany. ISBN 978-3-662-53745-9

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Official URL: https://link.springer.com/book/10.1007/978-3-662-5...

Abstract

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.

Item Type: Book
Subjects: K Law > K Law (General) > K7720 Recognition of foreign administrative acts
T Technology > TA Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics > TA1632.B35 Image processing--Digital techniques. Pattern recognition systems
Divisions: Faculty of Engineering > 21001-Engineering Science (S3)
Depositing User: Mr. Mahmud Basuki
Date Deposited: 21 Oct 2019 04:54
Last Modified: 21 Oct 2019 04:54
URI: http://repository.unsri.ac.id/id/eprint/12219

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