Thrown object detection method and system based on semantic segmentation network

A technology for semantic segmentation and detection methods, which is applied in image analysis, image enhancement, instruments, etc., and can solve problems such as high difficulty coefficient, inability to adapt to the transportation environment, and few sample materials.

Active Publication Date: 2020-12-08
NINGBO POLYTECHNIC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In the actual traffic scene, the forms of spilled objects are various, including cardboard boxes, wood, iron blocks, plastic shells, rain cloths, tire skins, etc., but because the amount of such materials is too small, if the direct Undoubtedly, it is very difficult to carry out training and learning on objects. Firs

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  • Thrown object detection method and system based on semantic segmentation network
  • Thrown object detection method and system based on semantic segmentation network
  • Thrown object detection method and system based on semantic segmentation network

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Embodiment 1

[0055]In order to make the detection of road spills quickly applicable to various environments and optimize the judgment method of spills, the present invention proposes a detection method of spills based on semantic segmentation network, which extracts sample data from real-time images , segment the non-moving target area in the road, combine the semantic segmentation network training for background comparison, and realize the detection of spilled objects, including three parts:

[0056] A1: In the offline modeling stage, collect sample data in each monitoring environment and monitoring video images at each time period, and use the semantic segmentation network to train and learn the sample data to obtain a road training model;

[0057] B1: In the online background acquisition stage, based on the background modeling method, the moving target extraction and ratio calculation are performed on the real-time image, and the preset background image and update coefficient are updated...

Embodiment 2

[0084] In order to have a better systematic understanding of the present invention, in addition to the description of the method steps in the first embodiment, the functional definition of the present invention is carried out through modular descriptions in this embodiment, such as figure 1 As shown, a sprinkler detection system based on semantic segmentation network, including offline modeling module, online background acquisition module and online sprinkler judgment module, wherein:

[0085] The offline modeling module is used to collect sample data in each monitoring environment and monitoring video images of each time period, and use the semantic segmentation network to train and learn the sample data to obtain a road training model;

[0086] The online background acquisition module is used to extract the moving target and calculate the ratio of the real-time image based on the method of background modeling, and update the preset background image and update coefficient acco...

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Abstract

The invention discloses a thrown object detection method and system based on a semantic segmentation network, and particularly relates to the field of road detection. The system mainly comprises an offline modeling module, an online background acquisition module and an online throwing judgment module. According to the method, the thrown object is indirectly judged through judgment of the moving target instead of direct judgment of the thrown object, the pre-detection rate of the thrown object is increased, and meanwhile, the preset background image is updated by adopting double backgrounds anda background updating strategy; and through similarity judgment of the candidate judgment area and the candidate judgment area and the preset background image, double judgment is carried out, so thatthe judgment accuracy is improved.

Description

technical field [0001] The invention relates to the field of road detection, in particular to a method and system for detecting spilled objects based on a semantic segmentation network. Background technique [0002] With the development of road traffic, the speed of inter-city transportation has been greatly increased. However, more and more freight vehicles have also caused many problems. In addition to frequent rear-end collisions and collisions, there are also vehicles to avoid falling cargo. Therefore, in addition to regulating driving behavior, the detection of accidental spills is also an important reference factor for traffic safety. [0003] Most of the existing detection methods for spilled objects on traffic roads use the traditional manual feature extraction method for detection, such as SIFT corner feature, LBP texture feature, etc. This method is affected by human factors. When changing the monitoring scene, the feature Insufficient generalization ability, weak...

Claims

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Application Information

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IPC IPC(8): G06T7/215G06T7/254
CPCG06T7/215G06T7/254G06T2207/10016G06T2207/20081G06T2207/20224G06T2207/30232G06T2207/30236
Inventor 陈文明
Owner NINGBO POLYTECHNIC
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