Our work in this area focuses upon hardware and software-based solutions to problems in ecology and entomology. Of particular interest is the development of computer-aided taxonomy tools for automated identification of species using bioacoustic signal processing, image processing and other techniques. Current research is aimed at developing tools for biodiversity informatics, tools for rapid detection of quarantine taxa (insects and plant pathogens) and hand-held species identification systems. Other research projects include automated identification of urban soundscapes in three dimensions, acoustic identification of vehicles and the development of biotelemetry systems.
Members: D. Chesmore
The Long-winged Conehead (Conocephalus fuscus) is expanding its range in the UK and has just reached Yorkshire. Monitoring of the insect is difficult because it lives in marshy and boggy habitats. This project will build dataloggers capable of detecting the singing of the male bush-crickets and log their activity as well as environmental parameters.
Members: Dave Chesmore
The identification of species is of paramount importance for ecological studies such as habitat fragmentation, bioindicator studies and biodiversity assessment. At present, surveys are carried out manually, are time consuming and rely on the surveyor’s expertise. This project aims to develop algorithms to enable people with smartphones to automatically identify the different British species.
Members: M.Z. Ayob, D. Chesmore
The recent invasion of the Harlequin Ladybird (Harmonia axyridis) into the UK has the potential for significant negative effects on populations of native species. The project is developing image processing methods for identifying Harlequin ladybirds from images supplied by the public in order to reduce the significant effort required by experts to sort through the many thousands of images obtained each year. In addition, the project aims to develop a system fro identifying the majority of native species.
Members: James Schofield, Dave Chesmore
With increasing global trade the risk of accidental introduction of non-native species is greater than ever. Such invasions can have a major impact both environmentally and economically; therefore action must be taken to prevent the introduction of such pests when importing goods. Estimates place the annual cost of invasive species in the United States at over $140 billion. The aim of this project is to develop a system to aid the work of Defra Plant Health & Seeds Inspectors (PHSI) in detecting non-native species within goods imported into the country. The system is intended to perform non-invasive real-time automated detection and classification of insect larvae in hard wood by utilising sounds produced as the larvae eat. This work is in collaboration with Central Science Laboratory, York.
Members: D. Chesmore
ANOPLORISK is a large EU project to investigate detection methods for invasive beetles, namely Asian and Citrus Longhorn beetles. They have the potential for considerable destruction of native trees and can be imported in live trees and wooden materials as larvae. The larvae are not easily detected. York's contribution to the project is to further develop and refine acoustic detection methods for the larvae by robustly detecting bites which are very short in duration.
Members: Naoko Evans, Dave Chesmore
Automated acoustic vehicle recognition has been studied in relation to various practical application areas such as; surveillance for security purposes, traffic monitoring and/or control as well as road planning, and also automated driver assistance systems, etc. Although the future goal of the project would be to develop a vehicle recognition system that employs multiple sensors in order to achieve a high accuracy, so far the work at University of York has concentrated on using acoustic and seismic sensors.
Members: Dave Chesmore, Jing Dai
This project has now finished. There is a serious and increasing taxonomic impediment caused primarily by a lack of trained taxonomists. Computer aided taxonomy (CAT) is one possible way of solving the problem by speeding up and partially automating the identification of taxa. The work described in this thesis develops a new CAT technique which performs semi-automated identification of two groups of insects: hoverflies and bumblebees using images of their wings. A series of image processing algorithms have been designed to extract high quality venation diagrams via a user-friendly software package.