Nondestructive testing method for agricultural product quality indicators

Abstract

The invention discloses a nondestructive testing method for agricultural product quality indicators. The nondestructive testing method comprises the following steps: Step 1, building a machine visiondetecting platform, and then comprehensively collecting RGB images of agricultural products in a visual sensor; Step 2, carrying out image segmentation on the images collected in Step 1, then dividingregions of agricultural products with interest, and extracting the contours of fruits of the agricultural products; Step 3, with the contours of the fruits of the agricultural products extracted in Step 2, extracting a shape feature vector with a shape invariant feature extraction operator, so as to overcome the problem of different sizes, positions and orientations of the agricultural products;and Step 4, with the images of the agricultural products of different shapes collected in the Step 1 and the feature vector extracted in Steps 2 and 3, training a support vector machine to determine the optimal parameters and the detection accuracy of the support vector machine. According to the invention, the machine vision technology is adopted to realize the non-destructive detection of the quality of agricultural products, and the nondestructive testing method has a very high real-time property, is reasonable and has high detection accuracy.

Description

technical field [0001] The invention relates to a method for non-destructive detection of agricultural product quality indicators, and belongs to the field of detection methods and technologies. Background technique [0002] Agricultural products (such as peanuts, melon seeds, pine nuts, pistachios, walnuts, etc.) are mostly rich in oil and protein, and their quality is prone to change in the case of high moisture and strong metabolism. Scholars at home and abroad generally use sensory evaluation or comprehensive determination of acid value and peroxide value when testing the quality of agricultural products. The latter has been included in the national standard as an important indicator for testing the quality of shellfish agricultural products. However, when using the above methods for quality inspection, there will be some problems: the results of sensory evaluation are greatly affected by personal and environmental factors, and it is difficult to form a unified standard;...

AI Technical Summary

Problems solved by technology

However, when using the above methods for quality inspection, there will be some problems: the results of sensory evaluation are greatly affected by personal and environmental factors, and it is difficult to form a unified standard; The instrument is not easy to clean

However, these detection methods require a large amount of samples and a long detection time, and when detecting shell agricultural products, they must be shelled for detection, which brings great inconvenience to the actual operation.

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