Method and system for ship detection in video images under the influence of ocean waves based on deep learning

A technology for video image and ship detection, applied in the field of target detection, can solve the problems of manual intervention, lack of quantitative indicators of ship detection accuracy, and low detection accuracy, and achieve the effect of improving accuracy

Active Publication Date: 2021-03-02
ZHUHAI DAHENGQIN TECH DEV CO LTD
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AI Technical Summary

Problems solved by technology

However, the method used in this literature is a traditional method, and image feature selection requires manual intervention, which is highly subjective.
In addition, there is a lack of quantitative indicators for evaluating the accuracy of ship detection under the influence of sea waves in the literature
In recent years, in the research of target detection based on deep learning, the more popular method is YOLO, which has the advantage of being able to meet the needs of real-time detection, but this method is not applicable under the influence of ocean waves, and its detection accuracy is low

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  • Method and system for ship detection in video images under the influence of ocean waves based on deep learning
  • Method and system for ship detection in video images under the influence of ocean waves based on deep learning
  • Method and system for ship detection in video images under the influence of ocean waves based on deep learning

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Embodiment Construction

[0039] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0040] Embodiments of the present invention provide a video image ship detection method under the influence of waves. With reference to the accompanying drawings, the specific steps of the embodiments of the present invention are as follows:

[0041] Step a: Sample marking, including marking of ship data and sea wave data, and saving the marked data;

[0042] In the embodiment of the present invention, the video frame image in the monitoring video of the electronic fence is first marked with a labeling tool. The labeling tool is Labelme, and the marked target includes two types of ships and waves. The marked image is saved as a json file. Preferably, the marked file can be converted into a standard pascal voc2007 data set, which includes three files: Annotations, ImageSets, JPEGImages, wherein the Annotations folder stores the...

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Abstract

The present invention provides a method and system for detecting ships in video images under the influence of ocean waves based on deep learning. The video image data is marked, including the labeling of ship data and ocean wave data; the ROI of the region of interest is extracted to obtain the ships and easy objects in the image. The position information of the wave target confused with the ship; the ROI of the region of interest is arranged and combined in pairs, and the dual-branch convolutional neural network structure constructed includes an input layer, multiple hidden layers of two branches, and an output layer; Paired ROIs of the same category or ROIs of different categories are used as the network input, and the similarity measurement results of the two images are used as the target output. The characteristics of the paired images are learned through the dual-branch convolutional neural network structure, and the network parameters are adjusted until they are trained well. A deep learning network; for the video frame images in the ship monitoring system on the shore under windy conditions, the trained deep learning network is used to distinguish between waves and ship images to achieve ship detection under the influence of waves.

Description

technical field [0001] The invention belongs to the field of target detection, and specifically relates to a method for detecting ships in video images under the influence of ocean waves based on deep learning. Background technique [0002] As a part of object detection, ship detection has always been a hot topic in the field of computer vision and pattern recognition. In many applications such as marine security, maritime monitoring and management, ship detection can provide decision-making information for it. [0003] Traditional target detection is usually based on machine learning, through artificial feature design, feature extraction, and inputting the extracted features into a classifier to achieve target detection tasks. With the development of deep learning, object detection has entered a new stage. Different from traditional artificially designed features, convolutional neural network (CNN) can automatically extract more representative features. Since no manual fe...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/32G06K9/62G06N3/04
CPCG06V20/41G06V10/25G06V2201/07G06N3/045G06F18/214
Inventor 邓练兵
Owner ZHUHAI DAHENGQIN TECH DEV CO LTD
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