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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-
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