1. PRECISION LIVESTOCK FARMING: CATTLE
IDENTIFICATION BASED ON BIOMETRIC DATA
By
Tarek Mahmmed Gaber, PhD
Faculty of Computers and Informatics
Suez Canal University
08/04/2014 – Faculty of Agriculture, Ismailia, Egypt

2. Scientific Research Group in Egypt
www.egyptscience.net

3. Overview
 Introduction
 Current work (cattle identification)
 Proposed System
 Experimental Results
 Conclusion

4. Introduction: What is the Problem
 Worldwide demand for meat is expected to increase with
>40% in next 15 years
 Health: Relationship between animal health and healthy
food
 Animal welfare
 Economic importance
 Others …….
 Source: [TIVO-project]

5. Introduction: Livestock Farm
Livestock farming in the past
The farmer spends some time
for noticing and monitoring

6. Livestock Farming Today
Experts do audio-
visual scoring by
visiting farms and
looking to 0behavior
of animal.

7. Precision Livestock Farming (PLF)
“ Management of livestock farming by continuous automated real-time
monitoring/controlling/tracing of production/reproduction, health and
welfare of livestock.”

8. Benefit for Farmers from PLF
 By automating the farming process, the farmer is
able to receive real-time information on his
livestock, so can:
 Manage and optimise animal production and welfare in
a fast and accurate way.

9. Research Area in PLF
 Examples of research points of PLF
 Monitoring feed times
 Feed in-take
 Condition scoring
 Real-time analysis of sound

10. Animal Tracing: Animal Identification
 Radio Frequency Identification
(RFID) is currently the most well used
method for animal identification.
 Ear tag or as a microchip the skin.
 Problems:
 Invasive and religious matters

11. Animal Biometric-based Solutions
 Can produce accurate results of cattle recognition in
real production conditions.
 Do not need to attach any additional elements with
or within the animals.
 Comply with most countries legal rules (e.g. the
current EU legislation) for beef traceability in
slaughterhouses.

12. Unique Features of Cattle
 Breeds muzzle pattern or
nose print has been
investigated and proven to be
unique for each cattle
 It is then concluded that
muzzle print is similar to the
human's fingerprint

13. Precision Livestock Farming: Cattle
Identification based on Biometric Data
 Training phase
 Collecting all training muzzle
print images.
 Extracting the features
 Representing each image by
one feature vector.
 Applying a dimensionality
reduction (e.g, LDA) to reduce
the number features in the
vector
 Testing phase
 Collecting the muzzle print
image,
 Extract the features
 Feature vector is projected on
LDA space.
 Applying machine learning
techniques for classifying the
test feature vector to decide
whether the animal is
identified or not).

15. Results
Accuracy results (in %) when applying our proposed
algorithm using different training images

16. Conclusion
 Precision Livestock farming could
 Increase the efficiency and sustainability for farming and
livestock production by monitoring (individual) animals
 Our proposal approach for cattle identification could
 Deliver quantitative information and complete traceability
of livestock in the food chain.
 Image-based identification could be a promising non-
intrusive method for cattle identification

17. Thanks