华南农业大学学报2024，Vol.45Issue(3)：390-396,7.DOI:10.7671/j.issn.1001-411X.202307014
基于三维点云的采后香蕉表征褐变定量评估方法
A quantitative evaluation method for postharvest banana characteristic browning based on the three-dimensional point cloud
摘要
Abstract
[Objective]To study the characteristic browning of postharvest bananas and evaluate the degree of senescence is very important for their fresh-keeping management.This study aims to solve the problems of high labor intensity and low efficiency of traditional methods for measuring the characteristic browning of bananas.[Method]A quantitative evaluation method of postharvest banana characteristic browning process based on three-dimensional point cloud was proposed.Firstly,three-dimensional point cloud model of banana was obtained by 3D scanner,and the geometric model of banana was reconstructed.Then the banana geometry model was denoised by point cloud filtering using euclidean clustering.The volume,surface area and dark spot area of banana were obtained by combining the image threshold segmentation method and Alpha Shapes.Finally,Fourier function was used to simulate the changing process of banana surface dark spots and determine the evaluation model of banana characteristic browning process.A comparison test was designed between the algorithm and the overflow method to measure the actual banana volume and the hand-drawn measurement area.[Result]By fitting the growth functions of different bananas,the fitting degree R2 of the regression line to the observed values was 0.9816>0.75,indicating the effectiveness of the algorithm.The comparison results showed that the average relative error between the proposed algorithm and the actual measured value was less than 1%,which verified the accuracy and feasibility of the proposed algorithm.[Conclusion]This study can provide data and technical support for banana preservation management.关键词
三维点云/数据拟合/香蕉/褐变/保鲜Key words
Three-dimensional point cloud/Data fitting/Banana/Browning/Fresh-keeping分类
信息技术与安全科学引用本文复制引用
熊俊涛,王雨杰,洪丹,梁俊浩,黄启寅..基于三维点云的采后香蕉表征褐变定量评估方法[J].华南农业大学学报,2024,45(3):390-396,7.基金项目
国家自然科学基金(32071912) （32071912）
