Pearl classification method based on depth learning

Abstract

Provided is a pearl classification method based on depth learning. The method includes the steps of 1) acquiring the pearl images as sample data; 2) preprocessing the sample data; 3) dividing the sample data into training data and test data; 4) using the training data to train the deep convolution network; 5) extracting the features of the training data and the test data by means of the trained deep convolution network; 6) constructing an SVM classifier by means of the features of the training data extracted in step 5) and classifying the test data by means of the SVM classifier. The depth learning is carried out by means of the multiple views of pearls, the self learning advantages of depth learning can be fully played, the good characteristics can be automatically learned, the tedious manual extraction of features and design features can be prevented, and moreover, the classification of the pearls is carried out through the combination of the SVM, and whether the pearls have threads can be effectively determined.

Description

technical field [0001] The invention relates to the technical fields of image processing and pattern recognition, in particular to a pearl classification method based on deep learning. Background technique [0002] China is a big producer of freshwater pearls, and its output accounts for 95% of the world's output. Among them, Zhuji City, Zhejiang Province is the largest base for freshwater pearl cultivation, processing and sales in my country, and its total output accounts for more than half of the country's total output. It is known as "Chinese Pearl". Town of". Zhuji's freshwater pearl cultivation area has reached 380,000 mu, and it has more than 1,500 pearl processing enterprises. [0003] After collecting a large number of pearls, most pearl enterprises need to manually classify the pearls in order to classify the pearls into different grades. Since manual classification will be affected by many factors, especially in the case of small pearls and large quantities, the c...

AI Technical Summary

Problems solved by technology

[0008] In order to overcome the problems that the existing pearl classification system based on machine vision is difficult to detect and classify the threads of pearls with high precision, and it is not easy to extract the thread features of pearls through manual design features, the present invention provides a pearl classification method based on deep learning , training a large amount of pearl image data through a deep convolutional network, learning the thread characteristics of pearls, and combining SVM to classify pearls, has a high recognition rate, good practicability, and good classification effect

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