Non-destructive detection method of fruit size based on orthogonal binocular machine vision

Abstract

The non-destructive detection method of fruit size based on orthogonal binocular machine vision uses two industrial cameras whose central axes are orthogonal to collect images of objects, and then preprocesses the collected images through MATLAB algorithms, extracts feature quantities, and calculates reasonable algorithms , to obtain the top-view standard contour map and the side-view standard contour map, and process the side-view standard contour map data to obtain the distance from the maximum fruit diameter surface to the bottom of the fruit, which is called the height of the fruit diameter surface. After processing the top-view standard contour map data, the calculated The fruit diameter, combined with the height of the fruit diameter surface, introduces the height proportional coefficient k, and corrects the calculated fruit diameter, that is, the fruit diameter with a small error is obtained, and then compared with the national fruit grading standard to realize the non-destructive measurement of the fruit size, which has standardization and efficiency. The characteristics of high precision, high precision and damage detection have important research significance.

Description

technical field [0001] The invention relates to the technical field of fruit detection, in particular to a nondestructive detection method for fruit size based on orthogonal binocular machine vision. Background technique [0002] At present, the classification of fruit size in China mainly relies on manual and mechanical implementation. The maximum axial diameter is measured by human eyes or vernier calipers as the fruit diameter. Due to the large difference in fruit shape, the maximum axial diameter is not easy to grasp. Manual grading errors are very large, and in the grading process, the work is cumbersome, the efficiency is low, and it is easy to cause serious damage to the fruit. At the same time, there are strong subjective factors. This kind of grading method can no longer meet the needs of fruit grading. [0003] In recent years, the detection method has gradually turned to the direction of machine vision, which can realize non-destructive testing, and has the charac...

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Problems solved by technology

[0002] At present, the classification of fruit size in China mainly relies on manual and mechanical implementation. The maximum axial diameter is measured by human eyes or vernier calipers as the fruit diameter. Due to the large difference in fruit shape, the maximum axial diameter is not easy to grasp. Manual grading errors are very large, and in the grading process, the work is cumbersome, the efficiency is low, and it is easy to cause serious damage to the fruit. At the same time, there are strong subjective factors. This kind of grading method can no longer meet the needs of fruit grading.

[0003] In recent years, the detection method has gradually turned to the direction of machine vision, which can realize non-destructive testing, and has the characteristics of high efficiency and high accuracy. Nowadays, machine vision technology is widely used in product classification, such as eggs, citrus, pears, etc. There are many varieties, different sizes and shapes, and less research on fruits with complex structures

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