A morphological modeling method and optical spectrum correction method of quasi-spherical fruits and vegetables

Abstract

The invention provides a spherical fruit and vegetable shape modeling method and an optical spectrum correction method. The morphological modeling method of spherical fruits and vegetables is as follows: first, according to the external contour characteristics of spherical fruits and vegetables, select the corresponding two-dimensional space curve for fitting, and determine a plurality of feature points on the two-dimensional curve for subsequent calculation of spherical fruits and vegetables. Fruit and vegetable morphological model parameters, the spherical-like fruit and vegetable morphological model is a three-dimensional surface model, which is obtained by rotating a two-dimensional space curve; then the image of the spherical-like fruit and vegetable is obtained with a camera, and after image processing operations such as background subtraction and binarization, the Establish a coordinate system on the image, obtain the coordinates of multiple feature points, substitute them into the three-dimensional surface model, and obtain multiple parameters in the three-dimensional surface model, so as to realize the real-time modeling of the spherical shape function of the fruit and vegetable surface. The spherical fruits and vegetables mainly include: apples, citrus, peaches, pears, tomatoes, potatoes and the like.

Description

technical field [0001] The invention relates to the field of detection of agricultural products of fruits and vegetables, and mainly relates to a spherical shape modeling method of fruits and vegetables and an optical spectrum correction method. Background technique [0002] my country is a big producer and consumer of fruit and vegetable agricultural products, but the current low level of post-harvest treatment restricts the development of corresponding industries. The lack of testing and grading links leads to uneven quality of corresponding commodities, which cannot meet consumers' consumption demand for high-quality fruit and vegetable agricultural products. It also makes exports less competitive. Improving the quality inspection and grading level of fruit and vegetable agricultural products is of great significance to improving commodity quality and ensuring food safety. [0003] As one of the main agricultural products of spherical fruits and vegetables, taking apples ...

AI Technical Summary

Problems solved by technology

[0004] There are technical difficulties in using image technology and spectral technology to detect apples. For example, in actual detection, under the action of the curvature of the apple surface, the reflected light is radial, and the reflected light received by the optical sensor only represents the reflected light information in one direction. , leading to errors in the collected spectral signals, and apples are not very regular spheres, the individual surface curvature of the sample is not constant, and it is difficult to accurately correct, resulting in differences in the acquired images and spectra for apples with the same internal and external quality; on the other hand, due to The size and shape of apples are different, and the distance between the light reflection point on the surface of the apple and the optical sensor cannot be kept constant, which increases the error in the image and spectral signals, and reduces the accuracy of quality prediction. correction method

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