The prediction of live weight from body measurements on female Holstein calves by digital image analysis

2012 ◽  
Vol 151 (4) ◽  
pp. 570-576 ◽  
Author(s):  
S. OZKAYA
Keyword(s):  
Image Analysis ◽  
Correlation Coefficient ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Live Weight ◽  
Regression Coefficients ◽  
Measuring System ◽  
Body Measurements ◽  
Age Regression ◽  
Holstein Calves

SUMMARYThe objective of the current study was to determine the accuracy of the prediction of live weight (LW) from body measurements (BMs) by using digital image analysis on female Holstein calves. The calves were measured with a measurement stick and digital image analysis. The following linear parameters were taken: body length (BL), wither height (WH), chest depth (CD), hip height (HH) and hip width (HW). LW and BMs were recorded at birth, at weaning and at 24 weeks of age. Regression coefficients, which included all BMs at birth, gave a low R2 value (66·7%), but the R2 value was found to be 87·6 and 86·0% at weaning and 24 weeks of age, respectively. A high correlation coefficient was found among LW and CD, HH and HW at weaning (0·90, 0·91 and 090, respectively) and at 24 weeks of age (0·89, 0·90 and 0·91, respectively). The results confirm that for female Holstein calves, digital image analysis is an effective measuring system for the prediction of LW from BMs.

Accuracy of body measurements using digital image analysis in female Holstein calves

2012 ◽  
Vol 52 (10) ◽  
pp. 917 ◽  
Author(s):  
Serkan Ozkaya
Keyword(s):  
Image Analysis ◽  
Body Length ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Digital Camera ◽  
Body Measurements ◽  
Analysis Software ◽  
High Prediction ◽  
Holstein Calves ◽  
The Difference

The objective of this study was to determine the accuracy of body measurements (BM) in Holstein female calves using digital image analysis. BM including body length, wither height, chest depth, hip height, and hip width of calves were recorded by stick and tape measurements at birth, weaning and 24 weeks of age. Then photos of calves were taken while calves were standing in a squeeze chute by a digital camera and were analysed by image analysis software to obtain BM of each calf from the image in centimetres. After comparing the actual and predicted BM, the accuracy was determined as 71, 97 and 99% for body length, 69, 87 and 99% for wither height, 43, 98 and 99% for chest depth, 74, 99 and 99% for hip height and 53, 99 and 98% for hip width at birth, weaning and 24 weeks of age, respectively. The difference between actual and predicted BM was significant at birth (P < 0.01). Although there were numerical differences between actual and predicted BM, the differences were not significant at weaning and 24 weeks of age (P > 0.01). According to these results, the BM estimation of Holstein female calves using digital image analysis produced high prediction accuracy at weaning and 24 weeks of age, but not at birth. The data presented in this study indicate that the digital image analysis provides very close agreement and reality for prediction of BM of Holstein female calves.

Estimation of bodyweight from body measurements and determination of body measurements on Limousin cattle using digital image analysis

2016 ◽  
Vol 56 (12) ◽  
pp. 2060 ◽  
Author(s):  
Serkan Ozkaya ◽  
Wojciech Neja ◽  
Sylwia Krezel-Czopek ◽  
Adam Oler
Keyword(s):  
Image Analysis ◽  
Body Length ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Digital Camera ◽  
Body Measurements ◽  
Analysis Software ◽  
Body Area ◽  
Image Analysis Software

The objective of this study was to predict bodyweight and estimate body measurements of Limousin cattle using digital image analysis (DIA). Body measurements including body length, wither height, chest depth, and hip height of cattle were determined both manually (by measurements stick) and by using DIA. Body area was determined by using DIA. The images of Limousin cattle were taken while cattle were standing in a squeeze chute by a digital camera and analysed by image analysis software to obtain body measurements of each animal. While comparing the actual and predicted body measurements, the accuracy was determined as 98% for wither height, 97% for hip height, 94% for chest depth and 90.6% for body length. Regression analysis between body area and bodyweight yielded an equation with R2 of 61.5%. The regression equation, which included all body traits, resulted in an R2 value of 88.7%. The results indicated that DIA can be used for accurate prediction of body measurements and bodyweight of Limousin cattle.

Surface Displacement Measurement of Soil Mass by White Light Digital Image Analysis in Frequency Domain

2014 ◽  
Vol 915-916 ◽  
pp. 1234-1237
Author(s):  
Jun Jun Li ◽  
Xin Wei Yang ◽  
Wen Guang Shi
Keyword(s):  
Image Analysis ◽  
Frequency Domain ◽  
Digital Image ◽  
White Light ◽  
Digital Image Analysis ◽  
Surface Displacement ◽  
Soil Mass ◽  
Measuring System ◽  
Surface Displacements ◽  
Simple Measuring

The surface displacement of soil mass is an important standard for safety in civil engineering. In this paper, white light digital image analysis in frequency domain is introduced tomeasure surface displacement of soil mass. This method has the characteristics of whole-field, non-contact measurement and the simple measuring system and can obtain displacements by frequency domination correlation arithmetic. Surface displacements of soil mass are obtained by white light digital image analysis in frequency domain. Comparing the experimental results and the theoretical values, the little error exists and the usefulness of this method is certified.

Digital image analysis to estimate the live weight of broiler

2010 ◽  
Vol 72 (1) ◽  
pp. 48-52 ◽  
Author(s):  
Md. Bazlur R. Mollah ◽  
Md. A. Hasan ◽  
Md. A. Salam ◽  
Md. A. Ali
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Live Weight

Displacement Measurement of Supporting Structure in Foundation Pit by White Light Digital Image Analysis in Frequency Domain

2014 ◽  
Vol 568-570 ◽  
pp. 36-39
Author(s):  
Jun Jun Li ◽  
Xin Wei Yang ◽  
Yan Feng Li
Keyword(s):  
Image Analysis ◽  
Frequency Domain ◽  
Digital Image ◽  
White Light ◽  
Digital Image Analysis ◽  
Experimental Results ◽  
Measuring System ◽  
Foundation Pit ◽  
Supporting Structure ◽  
Simple Measuring

The supporting structure in foundation pit is very important in civil engineering and is used to support the whole foundation pit. Its diaplacement is directly related to the safety of buildings. White light digital image analysis in frequency domain has the advantages of whole-field, non-contact measurement and the simple measuring system and can obtain displacements by frequency domination correlation arithmetic. In this paper, the method was introduced to measure the displacements of supporting structure. The experimental results show the usability of the method for supporting structure in foundation pit.

Deformation Measurement of Concrete by White Light Digital Image Analysis in Frequency Domain

2010 ◽  
Vol 29-32 ◽  
pp. 496-501 ◽  
Author(s):  
Xin Wei Yang ◽  
Hong Gao Man ◽  
Rui Lan Tian
Keyword(s):  
Image Analysis ◽  
Frequency Domain ◽  
Digital Image ◽  
White Light ◽  
Digital Image Analysis ◽  
Poisson Ratio ◽  
Concrete Specimen ◽  
Measuring System ◽  
Axial Tension ◽  
Simple Measuring

White light digital image analysis in frequency domain is introduced to study concrete deformation. This method has the characteristics of whole-field, non-contact measurement and the simple measuring system and can obtain displacements by frequency domination correlation arithmetic. Displacements of concrete specimen under axial tension are obtained by white light digital image analysis in frequency domain and then strains and Poisson ratio are calculated. Comparing the experimental results and the theoretical values, the error was little and the effectiveness of this method is certified. The applications of different surface features of concrete are studied.

Digital Image Analysis of the Larynx

2000 ◽  
Vol 10 (2) ◽  
pp. 7-9
Author(s):  
Yaser Natour ◽  
Christine Sapienza ◽  
Mark Schmalz ◽  
Savita Collins
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis
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