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A multi-level image retrieval method

A technology of image retrieval and image, which is applied in the field of retrieval, can solve problems such as retrieval failure, image interference content, etc., and achieve the effect of reducing interference and achieving successful retrieval

Inactive Publication Date: 2019-04-23
珩鑫科技(北京)有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a multi-level image retrieval method aimed at overcoming the above-mentioned deficiencies in the prior art, which can effectively solve the problem of retrieval failure due to the presence of more disturbing content in the image

Method used

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  • A multi-level image retrieval method

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Experimental program
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Embodiment 1

[0041] A multi-level image retrieval method, comprising the following steps:

[0042] Step 1: Extract local feature points of all images in the image database;

[0043] The local feature points in the step 1 can be SIFT feature points, SURF feature points, ORB feature points, HOG feature points, FAST feature points, BRISK feature points or LBP feature points;

[0044] Step 2: Use the K-means clustering algorithm to cluster all the local feature points extracted in step 1 to obtain K cluster centers, where the value of K is K=1-1000;

[0045] Step 3: For each image in the database, calculate its local feature aggregation descriptor based on the local feature points extracted in step 1 and the K cluster centers obtained in step 2;

[0046] Step 4: For the retrieved image, extract its local feature points, and calculate the local feature aggregation descriptor of the image based on the K cluster centers obtained in step 2 (the method of calculating its local feature aggregation ...

Embodiment 2

[0055] On the basis of embodiment 1. In the step 7, the region of interest in the retrieved image can be selected manually, and can be set as a fixed region in the retrieved image by using a saliency detection method.

Embodiment 3

[0057] On the basis of embodiment 1. The specific method of step 3 is as follows:

[0058] Step 3-1: Calculate the class number of each feature point in the image:

[0059] (Formula 1)

[0060] in, Indicates the tth feature point of the image, , n represents the number of image feature points, Indicates the jth cluster center, and i indicates the obtained Class number;

[0061] Step 3-2: Calculate the residual vector for each cluster:

[0062] (Formula 2)

[0063] in, Indicates the i-th cluster center, Indicates the kth feature point belonging to the i-th cluster in the image, and m indicates the total number of feature points in the image belonging to the i-th cluster; Represents the residual vector of the i-th cluster;

[0064] Step 3-3: Combine the k residual vectors obtained in step 3-2 into a one-dimensional vector using the following formula:

[0065] (Formula 3)

[0066] Step 3-4: Perform power-law normalization on each component in the one-dimensional...

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Abstract

The invention discloses a multistage image retrieval method. The method comprises the following steps of extracting local feature points of all images in an image database; clustering to obtain K clustering centers; for each image in the database, calculating a local feature aggregation descriptor of the image; for the retrieval image, extracting local feature points of the retrieval image, and calculating a local feature aggregation descriptor; and calculating distances between the local feature aggregation descriptors of the retrieved image and the local feature aggregation descriptors of all the images in the database, wherein the database image corresponding to the minimum distance is the preliminary retrieved result image. According to the method, multi-stage retrieval is carried outon the retrieval image, on one hand, for the retrieval image without background content interference or with a small amount of background content interference, the direct retrieval can be achieved; and on the other hand, for the retrieval image with a large amount of background content interference, the interference of the background content can be effectively reduced, and the successful retrievalis realized.

Description

technical field [0001] The invention relates to a retrieval method, in particular to a multi-level image retrieval method. Background technique [0002] With the rapid development of computers and the Internet, image resources are becoming more and more abundant. How to accurately retrieve the images that users need from large-scale image resources has become a key problem that needs to be solved urgently. Therefore, to establish an accurate image retrieval method has become a current research hotspot. [0003] In the field of image retrieval, the Vector of Locally Aggregated Descriptor (VLAD) is widely used in large-scale image retrieval. This method first clusters all the feature points of the image in the image database, each cluster center is a visual vocabulary, and all the cluster centers together form a visual codebook; then, based on the visual codebook, the feature points of each image are Quantization, calculating the local feature aggregation descriptor that cha...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/535G06F16/532G06K9/32G06K9/46G06K9/62
CPCG06V10/25G06V10/443G06V10/462G06F18/23213
Inventor 史凌波刘文龙
Owner 珩鑫科技(北京)有限公司
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