A sample-based method of 3D reconstruction for plant leaf from single image or multiple images

Agricultural operations require simple, efficient and robust measurement method of three dimensional forms for the plant organs such as leaves to analyse other kinds of phenotype in detail on this basis. However, most of the existing sample-based methods reconstruct three dimensional shapes of the images for the objects of smooth surface and homogeneous materials, such as plastics, paints, ceramics, and metals, etc., rather than for the natural objects of convex-concave surfaces and varying albedo materials under the arbitrary natural lights. In this paper, it was found that the methods based on the prior model with photometric stereo superposed BRDF proposed can accurately realize the 3D modelling for plant leaf image and may reduce the cumulative error. With the differential gradient constraint and integral gradient constraint proposed, the unique solution for the normal vectors of all micro panels of the pixel projection on the leaf surface was matched by the first-order central difference equation and the iterations, and this process solved the ill-posed problem of BRDF. The experiment results showed that the average error between the height reconstructed results and the measured results of the real leaves’ height was 15% and the attenuation error was reduced by our method.