Paper
22 October 2010 Three-dimensional location of tomato based on binocular stereo vision for tomato harvesting robot
Rong Xiang, Yibin Ying, Huanyu Jiang, Yongshi Peng
Author Affiliations +
Abstract
Accurate harvesting depends on the order of the accuracy of 3D location for harvesting robot. The precision of location is lower when the distance between fruit and camera is larger than 0.8 m for the method based on binocular stereo vision. This is a big problem. In order to improve the precision of depth measurement for ripe tomato, two stereo matching methods were analyzed comparatively which were centroid-based matching and area-based matching. Their performances in depth measurement were also compared. Experiments showed that the relationship between distance and measurement was linear. Then, models of unitary linear regression (ULR) were used to improve the results of depth measurement. After correction by these models, the depth errors were in a range of -28 mm to 25 mm for centroid-based matching method and -8 mm to 15 mm for area-based matching method at a distance of 0.6 m to 1.15 m. It can be concluded that costs of computation can be decreased with the promise of good precision when the parallax of centroid which is acquired through centroid-based matching method is used to set the range of parallax for area-based matching method.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rong Xiang, Yibin Ying, Huanyu Jiang, and Yongshi Peng "Three-dimensional location of tomato based on binocular stereo vision for tomato harvesting robot", Proc. SPIE 7658, 5th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronic Materials and Devices for Detector, Imager, Display, and Energy Conversion Technology, 76582Z (22 October 2010); https://doi.org/10.1117/12.866933
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Cited by 2 scholarly publications.
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KEYWORDS
Image segmentation

Cameras

Distance measurement

Stereo vision systems

CCD cameras

Stereoscopic cameras

3D vision

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