Three-dimensional measurement and segmentation for soil/stubble

Chun-Wai Hui; Kim Chew Ng

doi:10.1117/12.198883

6 January 1995 Three-dimensional measurement and segmentation for soil/stubble

Chun-Wai Hui, Kim Chew Ng

Proceedings Volume 2345, Optics in Agriculture, Forestry, and Biological Processing; (1995) https://doi.org/10.1117/12.198883
Event: Photonics for Industrial Applications, 1994, Boston, MA, United States

Abstract

This paper describes the measurement and range image processing of soil/stubble. The purpose of the data processing is to identify the data points corresponding to standing straw stubble from the soil surface in order that the erosion hazard of the soil can be studied. The 3D measurement system consists of a camera and a projector. A series of light stripes is projected onto the soil. By observing sample points on the camera image of the stripes on the soil surface, the relative positions of the corresponding points on the soil surface can be calculated. The system measures up to 8000 sample points in about half a minute. Intuitively, if the soil surface is aligned to a horizontal surface, the samples on the straws correspond to points with high altitudes. Thus, the first step in the processing is to construct the underlying soil surface. By comparing the difference in the height of the samples and the constructed soil surface, the samples corresponding to the straws can be identified. Discrete cosine transform low-pass filtering and morphological opening are examined for the soil surface construction. It is shown by simulation that the morphological opening provides much better results. The algorithm with morphological opening is also tested with measurement data. Preliminary results show that the algorithm provides a workable way to segment soil surface data and stubble data from the measurement.

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Chun-Wai Hui and Kim Chew Ng "Three-dimensional measurement and segmentation for soil/stubble", Proc. SPIE 2345, Optics in Agriculture, Forestry, and Biological Processing, (6 January 1995); https://doi.org/10.1117/12.198883

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KEYWORDS

Image filtering

Soil science

Spherical lenses

Cameras

Linear filtering

Image processing

Projection systems

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