Abstract
The paper highlights the substantial potential for digitalization in animal husbandry. Current applications of digital technologies include replacing manual data collection on animal phenotypes, particularly linear measurements of physical traits. In creating a contactless digital monitoring system for cattle exterior traits, cameras play a crucial role, as they enable accurate distance measurement to the object. Digital reconstruction of animal body morphometry using a contactless measurement method and automated size determination can effectively address the issues with inaccuracy and subjectivity associated with traditional scoring methods. (Research purpose) The study aims to explore the feasibility of using stereo cameras to measure object distances with the required accuracy and to analyze the performance of the stereo vision system across different areas of the frame. (Materials and methods) The study used a stereo pair of two 1/3-Inch CMOS OV4689 4-megapixel lenses mounted on the board, spaced at 6.3 centimeters from each other. Accurate distance measurement was considered achieved when the error remained within 1-2 percent (1-2 centimeters) of the object's distance (0.5-1 meter). A marked sheet with 25 centimeter intervals served as a test stand, and the stereo cameras captured the stand from distances of 30 to 100 centimeters, with a 10 centimeter increments. (Results and discussion) The study employed two camera configurations over two stages: a single stereo camera and a block of three cameras. Filming results with the single stereo camera showed a measurement error of 5-10 centimeters at distances ranging from 0.3 to 1 meter from the object. For the three-camera block, the accuracy remained comparable. It was found that accuracy was higher at the center of the frame, with an average error of 3 centimeters at viewing angles near zero.(Conclusions) The study confirmed that the number of stereo pairs does not impact accuracy, and the observed error represents the accuracy limit for these stereo pairs in stereo vision applications.
Published Version
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