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  1. University of Information Technology
  2. Faculty of Information Science

Automatic Assessing Body Condition Score from Digital Images by Active Shape Model and Multiple Regression Technique

http://hdl.handle.net/20.500.12678/0000005410
http://hdl.handle.net/20.500.12678/0000005410
2099a7ef-0602-45e7-926a-12f3c072d844
02499ff2-6c8f-4fca-b6c6-eaf1605b420b
Publication type
Conference paper
Upload type
Publication
Title
Title Automatic Assessing Body Condition Score from Digital Images by Active Shape Model and Multiple Regression Technique
Language en
Publication date 2017-01-22
Authors
Nay Chi Lynn
Thi Thi Zin
Ikuo Kobayashi
Description
Body Condition Score (BCS) of a dairy cow is a magnificent indicator for determining energy reserves of cows. The
purpose of this study is to assess BCS of dairy cattle by analyzing cows’ rear-view images. In order to do so, we first
model shape of cow’s tailhead area by using active shape model. Then, angle features are modelled as multiple
regression model for estimating scores. The experimental results show that proposed system is promising compared
to some existing methods.
Keywords
Body Condition Score, Active Shape Model, Multiple Regression Analysis, Angle features
Identifier 10.5954/icarob.2017.os20-3
Conference papers
ICAROB
19-22 January, 2017
The 2017 International Conference on Artificial Life and Robotics
Seagaia Convention Center, Miyazaki, Japan
https://alife-robotics.co.jp/LP/2017/OS20-3.htm
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