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Improving the Backlight Compensation Method in Optical 3D Scanning Systems for Livestock Buildings Based on a Python Algorithmic Implementation
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DOI：10.1134/s1063785026700549.png)
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Abstract
En 中文
This paper examines the physical mechanisms of interference during optical 3D scanning under conditions of intense stray light typical of livestock buildings. A refined physical model of noise generation in the signal from time-of-flight cameras has been developed, taking into account the scattering anisotropy in biological tissues and the influence of thin wet films on the surface of objects. Based on this model, a combined method for backlight compensation has been proposed that combines spectral selection (operating wavelength of 940 nm), synchronous detection with adaptive phase adjustment, and algorithmic correction by solving the inverse scattering problem in the diffusion approximation. The method is implemented as a modular software package in Python, optimized for operation on embedded computers. Experimental studies on a cow-udder simulator under combined illumination conditions (solar simulator + LED lighting) demonstrated a 63% reduction in the root-mean-square depth estimation error and a 3.3-fold increase in the signal-to-noise ratio from 8.2 to 18.7 dB, compared to traditional spectral filtering. The average processing time for a single 224 & times; 171 pixel frame was 85 ms on a Raspberry Pi 5 single-board computer, confirming the method's applicability to real-time systems.
Keywords:
time-of-flight camera
light scattering
diffusion approximation
inverse problem
software implementation
Python
backlight compensation
livestock buildings
Journal
T
IF:
0.9
Papers:
38
Citations:
1.9K
