Estimating pig weights from images without constraint on posture and illumination

Abstract This paper proposes an image based pig weight estimation method different from the previous works in three ways. The first difference is no constraint on pig posture and image capture environment, reducing the stress of the pigs. The second one is that the features obtained from 2D images are used without depending on 3D depth information. And the third is that our estimation model is constructed by exploiting the recent advances in machine learning. Besides the pig area size which had been a major feature parameter for the estimation, two new features, curvature and deviation, are introduced because those are related with the postures, thus being able to quantify the weight adjustment. A set of experiments are conducted to investigate how the performance is affected by the combination of the features and the neural network configurations. By using 477 training and 103 test images, the average estimation error of 3.15 kg was achieved, and the coefficient of determination of the model was R 2 = 0.79 .

[1]  Ilan Halachmi,et al.  Automatic assessment of dairy cattle body condition score using thermal imaging , 2013 .

[2]  Yongwha Chung,et al.  Automatic Recognition of Aggressive Behavior in Pigs Using a Kinect Depth Sensor , 2016, Sensors.

[3]  Y. Wang,et al.  Walk-through weighing of pigs using machine vision and an artificial neural network , 2008 .

[4]  David Reiser,et al.  3-D Imaging Systems for Agricultural Applications—A Review , 2016, Sensors.

[5]  Jørgen Kongsro,et al.  Estimation of pig weight using a Microsoft Kinect prototype imaging system , 2014 .

[6]  Erik Jørgensen,et al.  Determination of live weight of pigs from dimensions measured using image analysis , 1996 .

[7]  Claudia Arcidiacono,et al.  The automatic detection of dairy cow feeding and standing behaviours in free-stall barns by a computer vision-based system , 2015 .

[8]  Daniel Berckmans,et al.  The use of image analysis as a new approach to assess behaviour classification in a pig barn , 2013 .

[9]  R. D. Tillett,et al.  Shape measurements of live pigs using 3-D image capture , 2005 .

[10]  Sandra A. Edwards,et al.  Automatic detection of mounting behaviours among pigs using image analysis , 2016, Comput. Electron. Agric..

[11]  Jiahua Wu,et al.  Extracting the three-dimensional shape of live pigs using stereo photogrammetry , 2004 .

[12]  Andrea Pezzuolo,et al.  On-barn pig weight estimation based on body measurements by a Kinect v1 depth camera , 2018, Comput. Electron. Agric..

[13]  Stephen J. Searle,et al.  Weight estimation using image analysis and statistical modelling: a preliminary study , 2007 .

[14]  Toru Tamaki,et al.  A preliminarily study for predicting body weight and milk properties in lactating Holstein cows using a three-dimensional camera system , 2015, Comput. Electron. Agric..

[15]  Uwe Richter,et al.  Using machine vision for investigation of changes in pig group lying patterns , 2015, Comput. Electron. Agric..

[16]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[17]  J. A. Marchant,et al.  Monitoring pig growth using a prototype imaging system , 1999 .

[18]  Andrea Pezzuolo,et al.  A Feasibility Study on the Use of a Structured Light Depth-Camera for Three-Dimensional Body Measurements of Dairy Cows in Free-Stall Barns , 2018, Sensors.

[19]  B. Sturm,et al.  Implementation of machine vision for detecting behaviour of cattle and pigs , 2017 .

[20]  Yael Edan,et al.  Development of automatic body condition scoring using a low-cost 3-dimensional Kinect camera. , 2016, Journal of dairy science.

[21]  Federico Pallottino,et al.  Comparison between manual and stereovision body traits measurements of Lipizzan horses , 2015, Comput. Electron. Agric..

[22]  Daniel Berckmans,et al.  Comparison of a three-dimensional and two-dimensional camera system for automated measurement of back posture in dairy cows , 2014 .

[23]  Jan Urban,et al.  Application of machine vision systems in aquaculture with emphasis on fish: state-of-the-art and key issues , 2017 .

[24]  David J. Parsons,et al.  Real-time Control of Pig Growth through an Integrated Management System , 2007 .

[25]  Federico Pallottino,et al.  A low-cost stereovision system to estimate size and weight of live sheep , 2014 .

[26]  Nasser M. Nasrabadi,et al.  Pattern Recognition and Machine Learning , 2006, Technometrics.

[27]  J. R. Rosell-Polo,et al.  Advances in Structured Light Sensors Applications in Precision Agriculture and Livestock Farming , 2015 .

[28]  Daniel Berckmans,et al.  Classification of aggressive behaviour in pigs by activity index and multilayer feed forward neural network , 2014 .

[29]  Victor A. Kulikov,et al.  Application of 3-D imaging sensor for tracking minipigs in the open field test , 2014, Journal of Neuroscience Methods.

[30]  D. Stajnko,et al.  Estimation of bull live weight through thermographically measured body dimensions , 2008 .

[31]  Dries Berckmans,et al.  Precision livestock farming for pigs , 2017 .

[32]  Onur Yilmaz,et al.  Estimation of mature live weight using some body measurements in Karya sheep , 2012, Tropical Animal Health and Production.

[33]  Anders Krogh Mortensen,et al.  Weight prediction of broiler chickens using 3D computer vision , 2016, Comput. Electron. Agric..

[34]  Chen Shi,et al.  An approach of pig weight estimation using binocular stereo system based on LabVIEW , 2016, Comput. Electron. Agric..

[35]  Ke Wang,et al.  LSSA_CAU: An interactive 3d point clouds analysis software for body measurement of livestock with similar forms of cows or pigs , 2017, Comput. Electron. Agric..

[36]  Supachai Pathumnakul,et al.  An approach based on digital image analysis to estimate the live weights of pigs in farm environments , 2015, Comput. Electron. Agric..

[37]  G. C. Guarnera,et al.  Objective estimation of body condition score by modeling cow body shape from digital images. , 2011, Journal of dairy science.

[38]  J. A. Marchant,et al.  Pig growth and conformation monitoring using image analysis , 1999 .

[39]  Sakir Tasdemir,et al.  Original papers: Determination of body measurements on the Holstein cows using digital image analysis and estimation of live weight with regression analysis , 2011 .