Image retrieval method based on multi-feature and multi-relationship
An image retrieval, multi-feature technology, applied in multimedia data retrieval, multimedia data query, special data processing applications, etc., can solve problems such as unsatisfactory image retrieval results, and achieve the effect of accelerating speed, ensuring rationality, and improving accuracy
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[0024] In this embodiment, an image retrieval method based on multi-features and multi-relationships is to first use different image feature extraction methods to propose different features for the image; then use the multi-feature local voting method to perform feature fusion on the extracted different image features , to obtain a comprehensive feature; secondly, use the deep convolutional neural network to learn a better feature expression; use the k-means clustering method again to obtain different relational neurons, and design an objective equation; finally, use the BP algorithm to analyze the relational neurons The element is updated iteratively to complete the learning. Specifically, proceed as follows:
[0025] Step 1: Extract color, texture, shape and bag-of-words features from all images in the image data set X of size m×n, and obtain the features of size m×n respectively 1 The color feature dataset X 1 , the size is m×n 2 The texture feature image dataset X 2 , ...
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