Paper
16 April 2014 Automatic detection and segmentation of stems of potted tomato plant using Kinect
Author Affiliations +
Proceedings Volume 9159, Sixth International Conference on Digital Image Processing (ICDIP 2014); 915905 (2014) https://doi.org/10.1117/12.2064003
Event: Sixth International Conference on Digital Image Processing, 2014, Athens, Greece
Abstract
The automatic segmentation and recognition of greenhouse crop is an important aspect in digitized facility agriculture. Crop stems are closely related with the growth of the crop. Meanwhile, they are also an important physiological trait to identify the species of plants. For these reasons, this paper focuses on the digitization process to collect and analysis stems of greenhouse plants (tomatoes). An algorithm for automatic stem detection and extraction is proposed, based on a cheap and effective stereo vision system—Kinect. In order to demonstrate the usefulness and the potential applicability of our algorithm, a virtual tomato plant, whose stems are rendered by segmented stem texture samples, is reconstructed on OpenGL graphic platform.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Daichang Fu, Lihong Xu, Dawei Li, and Longjiao Xin "Automatic detection and segmentation of stems of potted tomato plant using Kinect", Proc. SPIE 9159, Sixth International Conference on Digital Image Processing (ICDIP 2014), 915905 (16 April 2014); https://doi.org/10.1117/12.2064003
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Cited by 3 scholarly publications.
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KEYWORDS
Image segmentation

Detection and tracking algorithms

Visualization

Agriculture

Image processing algorithms and systems

Binary data

Databases

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