A traffic billboard identification method based on an attention mechanism

A recognition method and billboard technology, applied in the field of computer vision, can solve problems such as untargeted area selection strategies, high time complexity, and redundant windows, and achieve the effects of reduced complexity, obvious detection speed, and high recognition efficiency

Inactive Publication Date: 2019-06-14
南京中设航空科技发展有限公司
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Problems solved by technology

There are two main problems in the traditional target detection task: one is that the region selection strategy based on the sliding window is not targeted, t

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  • A traffic billboard identification method based on an attention mechanism
  • A traffic billboard identification method based on an attention mechanism
  • A traffic billboard identification method based on an attention mechanism

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Embodiment Construction

[0033] The embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0034] Such as figure 1 , figure 2 As shown, an attention mechanism-based traffic billboard recognition method of the present invention, applied to an electronic device, includes the following steps:

[0035] S1: Input an original image, the size of the original image and the gray value range of each pixel are between 0-255;

[0036] S2: Since CNN is good at processing tensors with small values, and the size of the original image and the gray value range of each pixel are between 0-255, the original image is normalized and each image is converted It is a three-order tensor form: [height, width, channels], where height is the height of the normalized image, width is the width of the normalized image, and channels is the number of channels of the normalized image;

[0037] S3: Build an attention mechanism to learn the parts of the original image that...

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Abstract

The invention discloses a traffic billboard identification method based on an attention mechanism, which is applied to electronic equipment and comprises the following steps of: inputting an originalimage, and enabling the size of the original image and the gray value range of each pixel point to be in a range of 0-255; performing normalization on the original image, and converting each image into a third-order tensor form: [high, width, cannels]; constructing an attention mechanism, and learning the part, needing to be processed, of the original image; constructing a Faster RCNN multilayer neural network, and extracting and processing features of the image; according to a processing result, delineating a surrounding box of the advertising board. The multi-layer neural network is adopted,the attention mechanism is combined, the recognition score is increased nearby the two sides of the highway, the recognition score is reduced for the part away from the road surface, and therefore the recognition accuracy is improved, and the method has wide application prospects in the fields of image classification and target recognition.

Description

Technical field [0001] The invention belongs to the technical field of computer vision, and specifically relates to a traffic billboard recognition method based on an attention mechanism. Background technique [0002] The visual system is an important way for humans to perceive the world, and it is also the most profound part of human research understanding of themselves. Research has shown that 80% of external information is transmitted to the brain through the human visual system. In real life, people can easily achieve the purpose of perceiving the world through the visual system. Although the human visual system is very powerful, it is still necessary to develop computer vision that can simulate the human visual system. At present, computer vision technology has attracted more and more attention from scholars and has achieved rich results. However, it is still far away from the goal of perceiving information from the outside world like human vision. Target detection is an i...

Claims

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Application Information

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IPC IPC(8): G06K9/32G06N3/04
Inventor 周敏朱志超王勇杨健曾元图尔荪艾力
Owner 南京中设航空科技发展有限公司
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