an image retrieval method
An image retrieval and image technology, which is applied in the field of image processing, can solve problems such as error-prone, single extended image features, and heavy manual labeling workload, so as to achieve accurate image retrieval and improve training accuracy
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[0051] (1) Use open source tools such as VLFeat to extract SIFT feature points for each checked image in the checked image database, and perform L2 normalization processing on the SIFT feature points (that is, change the L2 modulus length of the SIFT feature points to 1), and randomly sample Part of the feature points, and use the K-Means method to train D cluster centers, and all cluster centers form a D-dimensional dictionary;
[0052] (2) Use the D-dimensional dictionary obtained in the previous step to describe the features of the searched image and the query image, and obtain the D-dimensional feature vectors of the searched image and the query image respectively. Let Q be the feature vector of the query image, and I i (i=1,2,...,N) is the feature vector of the image to be checked;
[0053] (3) Use the convolutional neural network AlexNet to extract the 4096-dimensional image features of the last fully connected layer of the checked image, and perform feature description ...
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