Classification of Clean and Dirty Pighouse Surfaces Based on Spectral Reflectance

Mogens Blanke, Ian David Braithwaite, Guo-Qiang Zhang

Research output: Book/ReportReportResearchpeer-review

Abstract

Current pig house cleaning procedures are hazardous to the health of farm workers, and yet necessary if the spread of disease between batches of animals is to be satisfactorily controlled. Autonomous cleaning using robot technology offers salient benefits. This report addresses the feasibility of designing a vision based system to locate dirty areas and subsequently direct a cleaning robot to remove dirt. Novel results include the characterisation of the spectral reflectance of real surfaces and dirt in a pig house and the design of illumination to obtain discrimination of clean from dirty areas with a low probability of misclassification. A Bayesian discriminator is shown to be efficient to obtain a correct classification in this context. This report is a result of research conducted jointly by the Technical University of Denmark (DTU) and the Danish Institute of Agricultural Sciences (DIAS)
Original languageEnglish
Publication statusPublished - 2004

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