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Automating insect identification: exploring the limitations of a prototype system
Author(s) -
Weeks P. J. D.,
O’Neill M. A.,
Gaston K. J.,
Gauld I. D.
Publication year - 1999
Publication title -
journal of applied entomology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.795
H-Index - 60
eISSN - 1439-0418
pISSN - 0931-2048
DOI - 10.1046/j.1439-0418.1999.00307.x
Subject(s) - identification (biology) , biology , benchmark (surveying) , set (abstract data type) , ecology , computer science , cartography , programming language , geography
Automated identification systems based on computer image analysis technology provide an attractive, but as yet unexploited potential solution to the growing burden of routine species identifications presently faced by a dwindling community of expert taxonomists. DAISY (the Digital Automated Identification SYstem) is a prototype novel automated identification system, developed to explore this possibility. In its pilot phase, the DAISY algorithms were developed to discriminate five species of parasitic wasp, based on differences in their wing structure. Here, again using wing form, the ability of DAISY to discriminate amongst an order of magnitude more species – 49 species of closely related biting midges is examined. In so doing an attempt is made to establish a set of basic ‘benchmark’ tests of the efficacy, and weaknesses, of such an automated identification system.