Stereoscopic fish length measurements using neural networks

Authors

  • Carlo M. Orofeo Department of Physics, University of San Carlos
  • Rhodesa U. Cruzet Department of Physics, University of San Carlos
  • Michael Paul B. Kindica Department of Physics, University of San Carlos
  • Ben Zuidberg Department of Physics, University of San Carlos
  • Kees Karremans Vrije Universiteit Amsterdam, The Netherlands

Abstract

An existing stereoscopic technique employing neural networks has been used to measure the length of fishes.
Investigations prior to the actual measurements show that external parameters such as salinity and the orientation of the object with respect to the cameras have negligible effect on the measurements. With a total error less than 2 mm, our method is far better than conventional techniques.

SPP 2002 Proceedings Cover

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Published

2002-10-23

Issue

2002: Proceedings of the 20th Samahang Pisika ng Pilipinas Physics Congress

Section

Image and Signal Processing

License

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Upon acceptance of their manuscript, the Authors further agree to grant SPP the non-exclusive, worldwide, and royalty-free rights to record, edit, copy, reproduce, publish, distribute, and use all or part of the manuscript for any purpose, in any media now existing or developed in the future, either individually or as part of a collection.
All other associated economic and moral rights as granted by the Intellectual Property Code of the Philippines are maintained by the Authors.

How to Cite

[1]
“Stereoscopic fish length measurements using neural networks”, Proc. SPP, vol. 20, no. 1, pp. SPP–2002, Oct. 2002, Accessed: Mar. 29, 2026. [Online]. Available: https://proceedings.spp-online.org/article/view/SPP-2002-1F-04