A METHOD TO DEVELOP A COMPUTER-VISION BASED SYSTEM FOR THE AUTOMATIC DAIRY COW IDENTIFICATION AND BEHAVIOUR DETECTION IN FREE STALL BARNS
type: CreativeWork
description: In this thesis, a method to develop a computer-vision based system (CVBS) for the automatic dairy cow identification and behaviour detection in free stall barns is proposed. Two different methodologies based on digital image processing were proposed in order to achieve dairy cow identification and behaviour detection, respectively. Suitable algorithms among that used in computer vision science were chosen and adapted to the specific characteristics of the breeding environment under study. The trial was carried out during the years 2011 and 2012 in a dairy cow free-stall barn located in the municipality of Vittoria in the province of Ragusa. A multi-camera video-recording system was designed in order to obtain sequences of panoramic top-view images coming from the multi-camera video-recording system. The two methodologies proposed in order to achieve dairy cow identification and behaviour detection, were implemented in a software component of the CVBS and tested. Finally, the CVBS was validated by comparing the detection and identification results with those generated by an operator through visual recognition of cows in sequences of panoramic top-view images. This comparison allowed the computation of accuracy indices. The detection of the dairy cow behavioural activities in the barn provided a Cow Detection Percentage (CDP) index greater than 86% and a Quality Percentage (QP) index greater than 75%. With regard to cow identification the CVBS provided a CDP > 90% and a QP > 85%.
abstract: In this thesis, a method to develop a computer-vision based system (CVBS) for the automatic dairy cow identification and behaviour detection in free stall barns is proposed. Two different methodologies based on digital image processing were proposed in order to achieve dairy cow identification and behaviour detection, respectively. Suitable algorithms among that used in computer vision science were chosen and adapted to the specific characteristics of the breeding environment under study. The trial was carried out during the years 2011 and 2012 in a dairy cow free-stall barn located in the municipality of Vittoria in the province of Ragusa. A multi-camera video-recording system was designed in order to obtain sequences of panoramic top-view images coming from the multi-camera video-recording system. The two methodologies proposed in order to achieve dairy cow identification and behaviour detection, were implemented in a software component of the CVBS and tested. Finally, the CVBS was validated by comparing the detection and identification results with those generated by an operator through visual recognition of cows in sequences of panoramic top-view images. This comparison allowed the computation of accuracy indices. The detection of the dairy cow behavioural activities in the barn provided a Cow Detection Percentage (CDP) index greater than 86% and a Quality Percentage (QP) index greater than 75%. With regard to cow identification the CVBS provided a CDP > 90% and a QP > 85%.
author: ANGUZZA, UMBERTO
language: eng
keywords: cow, behavioural, activity, precision, livestock, farming, dairy, farming, object, recognition, computer, vision, techniques, digital, image
date published: 2012-12-10
date modified: 2026-07-24T01:34:58Z
provider: Università degli Studi di Catania
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Università degli studi di Catania

PropertyValue
property ID: Handle
value: https://hdl.handle.net/20.500.11769/587320