Tree DBH measurement method based on smartphone and machine vision technology.

Abstract

Aiming at the problems of high labor intensity and low efficiency, complicated operation and high cost of advanced equipment in the measurement of DBH in existing traditional forest resources, and proposing a method for measuring diameter at breast height (DBH) based on smartphone and machine vision technology, and combining with camera calibration, 3D reconstruction, machine vision, close-range photogrammetry, and other technologies. First, The original image is obtained by smartphone, and the visual saliency map of the preprocessed image is processing by using the lab color space model and 3×3 operator to convolving with image. Combining with the H component of the HSV (Hue, Saturation, Value) color model to enhance the color contrast part of the tree trunk in the image. The image segmentation algorithm is used to identify and obtain the target tree's contour in a natural environment. Then, an improved camera calibration model with nonlinear distortion terms is used to calibrate the camera's internal and external parameters. Finally, achieving reconstruction of a 3D world with camera parameters and two-dimensional image information is carried out to measure DBH at a height of 1.3 m. Experimental results indicated that within a certain range, the relative error of the DBH measurements was lower than 2.50%. This method has a high measurement accuracy, meeting the accuracy requirement of DBH measurement in forest resources investigation and could be applied in forestry resource surveys.