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A small target detection method based on region nomination

A small target detection and small target technology, applied in the field of image processing, can solve the problems of difficult detection of small target in images, and achieve the effect of reducing calculation amount, suppressing background noise, and simple network structure

Active Publication Date: 2021-10-26
SOUTH CHINA UNIV OF TECH
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  • Claims
  • Application Information

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Problems solved by technology

Therefore, it is very difficult to detect small objects in images.

Method used

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  • A small target detection method based on region nomination
  • A small target detection method based on region nomination
  • A small target detection method based on region nomination

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Embodiment Construction

[0051] The present invention will be further described below in conjunction with specific examples.

[0052] In the small target detection method based on region nomination provided in this embodiment, an RGB color standard image is input for detection. The complete process of the detection is as follows figure 1 , the complete neural network structure diagram used in the designed image small target detection is as follows figure 2 . When preprocessing the image file, use an algorithm to convert the image to be detected to a uniform size; next, use a 5-layer convolutional neural network to extract 5 layers of basic features from the image; then, the 4th and 5th layers of the image feature fusion; then use the region nomination network to generate small target region nominations on the fusion feature map; finally, map the nominated region generated by the region nomination network to the fusion feature map, and use the fully connected layer network on the nomination region f...

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Abstract

The invention discloses a small target detection method based on region nomination, comprising the steps of: 1) preprocessing the input image, converting the input image into a uniform size; 2) extracting the basic feature map of the image, and extracting the 5-layer feature map; 3) feature Fusion, fusing the feature maps of the 4th and 5th layers of the image; 4) Small target area nomination, using the area nomination network to generate small target area nominations; 5) Small target bounding box refinement and classification of small target areas. The method of the invention has the advantages of fast calculation speed, high recognition accuracy of small targets, good generalization performance of the method, and detection of general extremely small target areas.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a small target detection method based on region nomination. Background technique [0002] Target detection refers to the process of accurately locating the objects contained in the image from the image and identifying the category of the object. Small target detection refers to locating and identifying objects that contain only a small number of pixels in the image. Small target detection has a very high application prospect in the fields of driverless road sign recognition and personal carry-on item recognition in the security field. [0003] Specifically, target detection is to find out the position, size and category of all objects contained in the image from the image. Existing target detection methods include region-based convolutional neural network RCNN, Fast-RCNN, Faster-RCNN series neural networks, end-to-end convolutional neural network SSD, and YOLO ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/46G06K9/36G06N3/04
CPCG06V10/20G06V10/44G06N3/045
Inventor 张宇郑冬云郭炜强郑波关健创
Owner SOUTH CHINA UNIV OF TECH