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Image recognition method and device, computer device and computer-readable storage medium

An image recognition and computer program technology, applied in the field of computer vision, can solve the problems of accuracy and robustness, accuracy is not very high, affect recognition accuracy, etc., to achieve good robustness, improve recognition speed, reduce The effect of small computational complexity

Active Publication Date: 2018-04-03
SHENZHEN INTELLIFUSION TECHNOLOGIES CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] Most of the existing image recognition methods have certain shortcomings.
For example, recognition methods based on multi-regions and multi-features usually require feature vectors with high dimensions to be trained and predicted, and the computational complexity is high and the accuracy and robustness are easily affected
The use of RGB color space will be affected by lighting and shooting conditions, which will cause different features extracted from the same object under different shooting conditions, thus affecting the recognition accuracy
However, based on the color space histogram, it is easy to be disturbed when calculating the similarity, and whether it is the histogram intersection method or the distance calculation method, its accuracy is not very high, and the complexity of multi-region calculation is high

Method used

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  • Image recognition method and device, computer device and computer-readable storage medium
  • Image recognition method and device, computer device and computer-readable storage medium
  • Image recognition method and device, computer device and computer-readable storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0045] figure 1 It is a flow chart of the image recognition method provided by Embodiment 1 of the present invention. The image recognition method is applied to a computer device.

[0046] Such as figure 1 As shown, the image recognition method specifically includes the following steps:

[0047] 101: Perform region division on the query image and the database image.

[0048]The query image is the image that needs to be recognized or matched, and the database image is the image in the pre-established image library. The image recognition method is to compare the query image with the database image to determine whether the query image matches the database image, so as to confirm whether the content in the query image is consistent with the content in the database image. For example, when performing pedestrian recognition, the pedestrian image captured by the camera on the road is the query image, and the portrait database image of the traffic control system is the database im...

Embodiment 2

[0080] image 3 It is a structural diagram of the image recognition device provided by Embodiment 2 of the present invention. Such as image 3 As shown, the image recognition device 10 may include: an area division unit 301, a coordinate calculation unit 302, a clustering unit 303, and a matching unit 304.

[0081] The area division unit 301 is configured to perform area division on the query image and the database image.

[0082] The query image is the image that needs to be recognized or matched, and the database image is the image in the pre-established image library. The image recognition method is to compare the query image with the database image to determine whether the query image matches the database image, so as to confirm whether the content in the query image is consistent with the content in the database image. For example, when performing pedestrian recognition, the pedestrian image captured by the camera on the road is the query image, and the portrait databa...

Embodiment 3

[0114] Figure 4 It is a schematic diagram of a computer device provided by Embodiment 3 of the present invention. The computer device 1 includes a memory 20 , a processor 30 and a computer program 40 stored in the memory 20 and executable on the processor 30 , such as an image recognition program. When the processor 30 executes the computer program 40, the steps in the above image recognition method embodiment are realized, for example figure 1 Steps 101-104 are shown. Alternatively, when the processor 30 executes the computer program 40, it realizes the functions of the modules / units in the above-mentioned device embodiments, for example image 3 Units 301-304 in .

[0115] Exemplarily, the computer program 40 can be divided into one or more modules / units, and the one or more modules / units are stored in the memory 20 and executed by the processor 30 to complete this invention. The one or more modules / units may be a series of computer program instruction segments capable...

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Abstract

The invention discloses an image recognition method. The method includes: carrying out region division on a query image and a database image; calculating logarithmic relative RGB coordinates of each pixel point of each region of the query image and the database image; carrying out clustering on the pixel points in each region of the query image and the database image according to the logarithmic relative RGB coordinates of each pixel point of each region of the query image and the database image to obtain a clustering center of each region of the query image and the database image; and according to the cluster center of each region of the query image and the database image, determining whether the query image matches the database image. The invention also provides an image recognition device, a computer device and a readable storage medium. The method can realize fast image recognition of high robustness and high interference immunity.

Description

technical field [0001] The present invention relates to the technical field of computer vision, in particular to an image recognition method and device, a computer device and a computer-readable storage medium. Background technique [0002] Most of the existing image recognition methods have certain shortcomings. For example, recognition methods based on multi-regions and multi-features usually require feature vectors with high dimensions for training and prediction, which has high computational complexity and is easily affected by accuracy and robustness. The use of RGB color space will be affected by lighting and shooting conditions, which will cause different features extracted from the same object under different shooting conditions, thus affecting the recognition accuracy. However, based on the color space histogram, it is easy to be disturbed when calculating the similarity, and whether it is the histogram intersection method or the distance calculation method, the ac...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/46G06F17/30
CPCG06F16/583G06V10/56G06F18/22G06F18/23213
Inventor 杨茜牟永强
Owner SHENZHEN INTELLIFUSION TECHNOLOGIES CO LTD
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