Behavioral Discrimination in Chicken Flocks: A Camera-Based Movement Analysis for Distinguishing Normal and Scared Behaviors

Abstract

Assessing chicken behavior in coops is crucial for high-quality meat production and stress prevention. This paper introduces an innovative system for evaluating behavior in chicken flocks by integrating collective area and its rate of change, surpassing traditional metrics like individual chicken distance walked, velocity, and acceleration. The novelty lies in simultaneously using multiple methods, providing a nuanced understanding of chicken responses and enhancing precision in behavior discrimination. The proposed system utilizes camera-based movement analysis, employing procedural image processing and data association for early detection and intervention in closed cage systems. This cost-effective solution is accessible to local farmers, contributing to improved poultry farming practices. The hardware setup includes a camera with a 470 nm bandpass lens, yielding computable results suitable for procedural system processes, especially in streamlining thresholding image processing.