Novel and Automatic Rice Thickness Extraction Based on Photogrammetry Using Rice Edge Features.

Yuchen Kong,Jian Liu,Shenghui Fang,Renshan Zhu,Xianting Wu,Yan Gong,Yi Peng

doi:10.3390/s19245561

Abstract

The dimensions of phenotyping parameters such as the thickness of rice play an important role in rice quality assessment and phenotyping research. The objective of this study was to propose an automatic method for extracting rice thickness. This method was based on the principle of binocular stereovision but avoiding the problem that it was difficult to directly match the corresponding points for 3D reconstruction due to the lack of texture of rice. Firstly, the shape features of edge, instead of texture, was used to match the corresponding points of the rice edge. Secondly, the height of the rice edge was obtained by way of space intersection. Finally, the thickness of rice was extracted based on the assumption that the average height of the edges of multiple rice is half of the thickness of rice. According to the results of the experiments on six kinds of rice or grain, errors of thickness extraction were no more than the upper limit of 0.1 mm specified in the national industry standard. The results proved that edge features could be used to extract rice thickness and validated the effectiveness of the thickness extraction algorithm we proposed, which provided technical support for the extraction of phenotyping parameters for crop researchers.

Highlights

Rice is one of the most important food crops for humans [1]
An automatic extraction method of rice thickness based on edge features was proposed in this paper
The hypothesis that the average height of the edges of multiple rice is half of the thickness of rice was put forward, which transformed the target from the thickness of rice to the height of the edge, so the problem that the corresponding points of the highest points of rice cannot be directly matched due to the scare texture of rice surface was solved

Summary

Introduction

Rice is one of the most important food crops for humans [1]. About half of the people in the world depend on rice as their staple food [2]. A significant part of rice quality evaluation is the analysis of rice dimension parameters [3,4,5], such as length, width and thickness of rice kernel. Researchers have made a lot of progress in determining the genes that determine the length or width of rice [8], but in terms of thickness, there is little. The main reason is that there is no fast and efficient way to measure the thickness of rice. Scholars have become increasingly interested in crop phenotypes [9,10]

Objectives

Results

Conclusion