Small target detection method and system under low visibility

A technology for small target detection and low visibility, applied in the field of computer vision, it can solve the problems of high false alarm rate and low recall rate, and achieve the effect of abstract content, rich receptive field, and taking into account detection efficiency and accuracy.

Inactive Publication Date: 2020-02-18
EAST CHINA INST OF COMPUTING TECH
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Problems solved by technology

[0004] Domestic patent CN110097129A discloses a remote sensing target detection method based on contourlet grouping feature pyramid convolution, whi

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  • Small target detection method and system under low visibility
  • Small target detection method and system under low visibility
  • Small target detection method and system under low visibility

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[0035] The present invention will be described in detail below with reference to specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that, for those skilled in the art, several changes and improvements can be made without departing from the inventive concept. These all belong to the protection scope of the present invention.

[0036] Thanks to the rapid development of deep convolutional neural networks, the problem of object detection has gradually made great progress. However, due to the little information and low resolution of small targets in the image, especially in the case of low brightness, backlight, and blurred environment, there is more noise, so that after being extracted by the convolutional neural network, the characteristics are still very weak, so small target detection Difficulty and low precision. Among the existing...

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Abstract

The invention provides a small target detection method and system under low visibility. The method includes: taking RefineDet as a detector, and processing the target image by adopting multi-scale retinal enhancement with color restoration to obtain an enhanced image; filtering a negative anchor point in the enhanced image by using the anchor point refining model, establishing an association relationship between the anchor point refining model and the target detection model, sharing a feature image in the anchor point refining model to the target detection model based on the association relationship for regression and category prediction, and outputting an identification result. Under the conditions of low brightness, backlight and fuzzy environment, a multi-scale retina enhancement algorithm with color recovery is adopted to reduce the sensitivity of the image under different illumination, reduce noise and improve the characteristics of the small target after being extracted by the convolutional neural network; through fusion of the high-level semantic features and the low-level features, the features with rich receptive fields, sufficient details and abstract content are obtained, and the discrimination degree of small targets is improved.

Description

technical field [0001] The present invention relates to the technical field of computer vision, in particular to a small target detection method and system in low visibility. Background technique [0002] The small target problem has always been a difficulty in visual tasks such as object detection and semantic segmentation. The detection accuracy of small targets is usually only half of that of large targets. In the MS COCO dataset, a small target is defined as an object with an area smaller than 32*32. Due to the low resolution, blurred images and less information carried by small targets, the feature expression ability is weak, and it is difficult to extract more effective features, making it difficult to detect small targets. At present, the more popular methods to solve the problem of small target detection are the scale enlargement method, which is to enlarge the image before detection; the Anchor window improvement method, which is to improve the density, range and s...

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Application Information

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IPC IPC(8): G06K9/00G06K9/40G06K9/46G06K9/62G06N3/04
CPCG06V20/00G06V10/30G06V10/454G06V2201/07G06N3/045G06F18/253
Inventor 高明柯杜欣军逄涛王熠郭威刘鹏飞冒睿瑞张浩博于楠
Owner EAST CHINA INST OF COMPUTING TECH
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