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Machine Vision and Applications manuscript No. (will be inserted by the editor)

Summary: Machine Vision and Applications manuscript No.
(will be inserted by the editor)
Natalia Larios Hongli Deng Wei Zhang Matt Sarpola Jenny Yuen
Robert Paasch Andrew Moldenke David A. Lytle Salvador Ruiz
Correa Eric N. Mortensen Linda G. Shapiro Thomas G. Dietterich
Automated Insect Identification through Concatenated
Histograms of Local Appearance Features
Feature Vector Generation and
Region Detection for Deformable Objects
Received: date / Accepted: date
Abstract This paper describes a computer vision ap-
proach to automated rapid-throughput taxonomic iden-
tification of stonefly larvae. The long-term goal of this
research is to develop a cost-effective method for environ-
mental monitoring based on automated identification of
indicator species. Recognition of stonefly larvae is chal-
lenging because they are highly articulated, they exhibit
a high degree of intraspecies variation in size and color,
and some species are difficult to distinguish visually, de-
spite prominent dorsal patterning. The stoneflies are im-


Source: Anderson, Richard - Department of Computer Science and Engineering, University of Washington at Seattle


Collections: Computer Technologies and Information Sciences