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Home / Equine Research Bank / J Equine Sci / 3D imaging and body measurement of riding horses using four ...
Journal of equine science2024; 35(1); 1-7; doi: 10.1294/jes.35.1

3D imaging and body measurement of riding horses using four scanners simultaneously.

Abstract: Although there have been advances in the technology for measuring horse body size with stereoscopic three-dimensional (3D) scanners, previously reported methods with a single scanner still face a significant challenge: the time necessary for scanning is too long for the horses to remain stationary. This study attempted to scan the horse simultaneously from four directions using four scanners in order to complete the scans in a short amount of time and then combine the images from the four scans on a computer into one whole image of each horse. This study also compared body measurements from the combined 3D images with those taken from conventional manual measurements. Nine riding horses were used to construct stereoscopic composite images, and the following 10 measurements were taken: height at the withers, back, and croup; chest depth; width of the chest (WCh), croup, and waist; girth circumference, cannon circumference (CaC), and body length. The same 10 measurements were taken by conventional manual methods. Relative errors ranged from -1.89% to 7.05%. The correlation coefficient between manual and 3D measurements was significant for all body measurements (P<0.01) except for WCh and CaC. A simple regression analysis of all body measurements revealed a strong correlation (P<0.001, R=0.9994, root-mean-square error=1.612). Simultaneous scanning with four devices from four directions reduced the scanning time from 60 sec with one device to 15 sec. This made it possible to perform non-contact body measurements even on incompletely trained horses who could not remain stationary for long periods of time.
©2024 The Japanese Society of Equine Science.
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Publication Date: 2024-03-19 PubMed ID: 38524754PubMed Central: PMC10955269DOI: 10.1294/jes.35.1Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This study investigates the use of four stereoscopic 3D scanners to quickly and accurately measure a horse’s body size. Achieving accurate measurements without the horse having to remain still for long periods, the study compares results with traditional manual methods and finds significant correlations, with exceptions noted in chest width and cannon circumference.

Research Objective

  • The purpose of this study was to circumvent the challenge posed by single scanner measurement techniques, where extended time for scanning often complicates the process as horses can’t stay stationary for long periods. The research aimed to scan a horse’s body from four different directions using four scanners simultaneously to complete the task in a fraction of the time.

Methodology

  • Nine riding horses were used for the research. Their bodies were scanned by four 3D scanners strategically positioned to capture the horse’s body from four different angles simultaneously. The digital images acquired from the four scans were then combined on a computer to render a single composite image for each horse.
  • The team took ten measurements: height at the withers, back and croup; chest depth; width of the chest (WCh), croup and waist; girth circumference, cannon circumference (CaC), and body length. These were then compared with the measurements obtained from conventional manual methods.

Results

  • The relative errors recorded ranged between -1.89% and 7.05% when comparing the 3D scans and manual measurements.
  • Correlation coefficients showed a statistically significant correlation between the 3D and manual measurements for all body measurements except for chest width (WCh) and cannon circumference (CaC).
  • The regression analysis indicated a strong correlation between all body measurements with a root-mean-square error of 1.612, validating the accuracy of the 3D scanning system employed.

Time Efficiency

  • One of the primary goals was to reduce the scanning time without compromising on accuracy. The study established that using four scanners simultaneously reduced the scanning time from 60 seconds to 15 seconds – a significant improvement, making it feasible to measure horses that aren’t trained to stay stationary for extended periods.

Cite This Article

APA
Matsuura A, Torii S, Ojima Y, Kiku Y. (2024). 3D imaging and body measurement of riding horses using four scanners simultaneously. J Equine Sci, 35(1), 1-7. https://doi.org/10.1294/jes.35.1

Publication

Journal of equine science
ISSN: 1340-3516
NlmUniqueID: 9503751
Country: Japan
Language: English
Volume: 35
Issue: 1
Pages: 1-7

Researcher Affiliations

Matsuura, Akihiro
  • Department of Animal Science, School of Veterinary Medicine, Kitasato University, Aomori 034-8628, Japan.
Torii, Suzuka
  • Department of Animal Science, School of Veterinary Medicine, Kitasato University, Aomori 034-8628, Japan.
Ojima, Yuki
  • Department of Animal Science, School of Veterinary Medicine, Kitasato University, Aomori 034-8628, Japan.
Kiku, Yoshio
  • Department of Sustainable Agriculture, College of Agriculture, Food and Environment Sciences, Rakuno Gakuen University, Hokkaido 069-8501, Japan.

References

This article includes 17 references
  1. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 327: 307–310.
    pubmed: 2868172
  2. Carroll CL, Huntington PJ. Body condition scoring and weight estimation of horses. Equine Vet. J. 20: 41–45.
    pubmed: 3366105
  3. Catalano DN, Coleman RJ, Hathaway MR, Neu AE, Wagner EL, Tyler PJ, McCue ME, Martinson KL. Estimation of actual and ideal bodyweight using morphometric measurements of miniature, saddle-type, and Thoroughbred horses. J. Equine Vet. Sci. 78: 117–122.
    pubmed: 31203974
  4. Le Cozler Y, Allain C, Caillot A, Delouard JM, Delattre L, Luginbuhl T, Faverdin P. High-precision scanning system for complete 3D cow body shape imaging and analysis of morphological traits. Comput. Electron. Agric. 157: 447–453.
  5. Fischer A, Luginbühl T, Delattre L, Delouard JM, Faverdin P. Rear shape in 3 dimensions summarized by principal component analysis is a good predictor of body condition score in Holstein dairy cows. J. Dairy Sci. 98: 4465–4476.
    pubmed: 25958280
  6. Hoffmann G, Bentke A, Rose-Meierhöfer S, Ammon C, Mazetti P, Hardarson GH. Estimation of the body weight of Icelandic horses. J. Equine Vet. Sci. 33: 893–895.
  7. Huang L, Li S, Zhu A, Fan X, Zhang C, Wang H. Non-contact body measurement for Qinchuan cattle with LiDAR sensor. Sensors (Basel) 18: 3014.
    pmc: PMC6164280pubmed: 30205607
  8. Huang L, Guo H, Rao Q, Hou Z, Li S, Qiu S, Fan X, Wang H. Body dimension measurements of Qinchuan cattle with transfer learning from LiDAR sensing. Sensors (Basel) 19: 5046.
    pmc: PMC6891291pubmed: 31752400
  9. Jones RS, Lawrence TLJ, Veevers A, Cleave N, Hall J. Accuracy of prediction of the liveweight of horses from body measurements. Vet. Rec. 125: 549–553.
    pubmed: 2603337
  10. Li J, Ma W, Li Q, Zhao C, Tulpan D, Yang S, Ding L, Gao R, Yu L, Wang Z. Multi-view real-time acquisition and 3D reconstruction of point clouds for beef cattle. Comput Electron Agric 197: 106987.
  11. Martinson KL, Coleman RC, Rendahl AK, Fang Z, McCue ME. Estimation of body weight and development of a body weight score for adult equids using morphometric measurements. J. Anim. Sci. 92: 2230–2238.
    pubmed: 24663191
  12. Matsuura A, Dan M, Hirano A, Kiku Y, Torii S, Morita S. Body measurement of riding horses with a versatile tablet-type 3D scanning device. J. Equine Sci. 32: 73–80.
    pmc: PMC8437753pubmed: 34539208
  13. Murray JMD, Bloxham C, Kulifay J, Stevenson A, Roberts J. Equine nutrition: a survey of perceptions and practices of horse owners undertaking a massive open online course in equine nutrition. J. Equine Vet. Sci. 35: 510–517.
  14. Oki H, Nagata Y. A study on growth on 24 body parts in the Thoroughbred. Bull. Epuine Res.Inst. 20: 16–26.
  15. Pérez-Ruiz M, Tarrat-Martín D, Sánchez-Guerrero MJ, Valera M. Advances in horse morphometric measurements using LiDAR. Comput. Electron. Agric. 174: 105510.
  16. Vieira PS, Nogueira CEW, Santos AC, Borba LDA, Scalco R, Brasil CL, Barros WS, Curcio BDR. Development of a weight-estimation model to use in pregnant criollo-type mares. Cienc. Rural 48: e20160590.
  17. Wagner EL, Tyler PJ. A comparison of weight estimation methods in adult horses. J. Equine Vet. Sci. 31: 706–710.

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