Red date quality sorting method based on deep learning

Abstract

The invention provides a red date quality sorting method based on deep learning. The method comprises the steps that a large quantity of red date samples with different quality are collected, the samples are divided into four types, namely plump dates, dry bar dates, cracked dates and blemished dates, and the samples are divided into a training set and a test set; collected red date sample imagesare preprocessed, wherein image processing operation, such as graying, binaryzation, median filtering and ROI area-of-interest extraction, is performed on the red date images on a white background, the red dates in the large white background are picked out, and the sizes of the sample images need to be normalized; and a network with an improved structure is used to train the sample training set toobtain a model, and the model generated through training is utilized to classify the test sample images. Compared with existing red date quality sorting technologies, through the method, the accuracyand speed of red date sorting are improved, and the problems that manual sorting of red dates is low in efficiency and accuracy and consumes excessive manpower resources are successfully solved.

Description

technical field [0001] The invention relates to a jujube quality classification method based on deep learning technology. The method includes machine vision technology, basic graphic image processing technology, deep learning and convolutional neural network. By extracting jujube features, it can accurately classify Jujube quality is classified. Background technique [0002] China is the country of origin of jujube, and it is also the largest jujube producer and the only exporter in the world. It owns more than 95% of jujube resources in the world and occupies a leading position in the world's jujube industry. Jujube is the most competitive agricultural product after my country's accession to the WTO. In recent years, my country's red jujube production has maintained an overall growth, with an annual output of 9.135 million tons in 2015. Jujube quality sorting is a key technical link in the storage, processing and circulation of jujube, which directly affects the economic ...

AI Technical Summary

Problems solved by technology

The quality of manual sorting of jujubes has disadvantages such as high labor intensity, low efficiency, high cost, and difficulty in guaranteeing sorting accuracy and hygienic quality.

Mechanical screening of jujubes. At present, the problems of mechanical screening of jujubes in the market are that the degree of intelligence is not high, the accuracy is low, and the sorting speed is slow.

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