UWE Bristol Engineering showcase 2015

Adam Drake
BEng(Hons) Robotics
Project Supervisor
Professor Melvyn Smith
Identification of Cattle using Computer Vision Biometrics
Introduction
Computer vision biometrics is a vast research topic
with many applications across an array of
industries. This investigation is in the area of
animal biometrics. Currently, the majority of
industrial animal identification tasks are
completed using a form of tagging, involving little
or no computer vision.
This investigation examined current
methodologies for computer vision biometrics, in
both human and animal applications, and
proposed a novel non-invasive method for the
identification of cattle. This investigation was part
of an ongoing project, the ‘Precision Health
Monitoring of Cattle’ by the Centre for Machine
Vision at the Bristol Robotics Laboratory.
Core Concept
The central idea to this investigation was that
hidden information contained within the animal
can be extracted.
Coat patterns were examined for their
‘uniqueness’ and it was thought that this would be
sufficient to describe an individual animal.
However, this approach was not robust enough
and suffered from problems such as different
lighting conditions and all-brown cattle displaying
no visible coat patterns.
The selected approach uses the actual geometry
of the animal to better satisfy the requirements of
the system to be robust enough to work with
cattle which have no discernible coat pattern.
Image Processing
In order to extract the required information, the
depth images had to be processed to remove the
background and additional unwanted details.
Then through a series of further image processing
steps, including a Gaussian low-pass filter, the
important parts of the depth image are revealed.
Benefits over Radio Frequency ID Tags
RFID tags in use for cattle identification have
several drawbacks. Firstly they have to be affixed
to the animal in some way, taking considerable
time and effort. Secondly, they suffer from
interference, due to the proliferation of multiple
standards and frequencies, leading to instances of
false-reading and inaccuracy.
Applications
This new method of cattle identification has the
potential to offer increased biosecurity on farms,
reduced labour and time costs associated with
current identification methods and improved
accuracy compared to traditional methods.
Project summary
The investigation presents a review of the
current state of cattle identification and
proposes a novel method for identifying cattle
based on their physical features.
Project Objectives
• Develop a method of identifying cattle
based upon some physical characteristic,
using 3D depth images obtained from a
dairy farm environment.
• Research methods of biometric feature
extraction.
• Perform image processing on images of
cattle.
• Research current computer vision
biometric techniques.
Project Conclusion
The proposed new method of identifying
cattle based upon their physical
characteristics performed well and was able
to extract a set of features for all animals in
the dataset. Recommendations were made
for how to integrate the system into other
applications.
It is proposed that this approach not be limited to
cattle and could be extended to work with many
different animals in the future. There is also the
potential to integrate this method of biometric
feature extraction with an artificial intelligence
algorithm, to further enhance its capabilities.