Computational Intelligence based construction of a Body Condition Assessment system for cattle

Abstract

The objective of this paper is to describe a Computational Intelligence based Automatic Body Conditioning System for cattle we have called Automatic Body Condition Assessment (ABiCA). It is an automatic body condition scoring system for dairy cattle that aims to overcome the flaws of the subjective and time consuming scoring task that is usually carried out by experts. No special set-ups are needed since the system uses pictures taken using normal hand-held cameras. ABiCA is split into two components. A first component for the segmentation of the rear-end shape of a cow from its picture through Active Shape Models Active Shape Models (ASMs) that are evolved using an evolutionary algorithm. The second component is in charge of estimating the Body Condition Score (BCS) of a cow from the shape provided by the ASM. Several classifiers and a symbolic regression function evolved by means of genetic programming techniques are tested for this task. The whole system is tested over a set of images coming from different cattle farms and its goodness provided in terms of the classifications obtained by a set of experts.