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Ocean State Calculation Method Based on Image Recognition

A state calculation and image recognition technology, applied in the direction of calculation, calculation model, computer parts, etc., can solve the problems of different judgment standards, inconsistent judgment results, difficult to popularize and apply on a large scale, and achieve a good theoretical and technical platform, broad Market prospect, effect of high recognition effect

Active Publication Date: 2020-08-14
TIANJIN UNIV
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Problems solved by technology

However, the existing methods of sea state estimation using images mainly rely on people to identify images. On the one hand, different judgment standards for different people can easily lead to inconsistent judgment results. On the other hand, such methods rely too much on human participation and are difficult to carry out. Large-scale promotion and application

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  • Ocean State Calculation Method Based on Image Recognition
  • Ocean State Calculation Method Based on Image Recognition
  • Ocean State Calculation Method Based on Image Recognition

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Embodiment Construction

[0016] The main content of the invention is to use the PCANet algorithm of deep learning to train a model capable of automatic image recognition and classification by collecting image libraries of different sea conditions, and to perform sea state recognition and classification on sea state images collected in real time.

[0017] The specific implementation steps are as follows:

[0018] The first step: data acquisition: this part mainly acquires two kinds of data, one is the sea state image data taken by the camera installed on the buoy, and the other is the sea wave and wind speed data obtained by the sensor at the same time in the same area. The data is used for sea state identification, and the wave and wind speed data are used as benchmark data for labeling of sea state levels. All data should be divided into two categories according to the idea of ​​machine learning: training samples and test samples. The training samples are used to train the machine learning model for...

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Abstract

The present invention relates to the field of sea state estimation of ocean observation. It utilizes the PCANet algorithm of deep learning to train a model capable of automatic image recognition and classification by collecting picture libraries of different sea states, and performs sea state recognition and classification on sea state images collected in real time. The technical solution adopted by the present invention is, the ocean state calculation method based on image recognition, the steps are as follows: the first step: data acquisition; the second step: image preprocessing: including image enhancement, image denoising, image normalization and image Segmentation; the third step: image feature extraction and recognition: specifically use PCANet's deep learning algorithm for image feature extraction and recognition; the fourth step: test and result analysis: use test samples to verify the accuracy of the training model. The invention is mainly applied to ocean observation.

Description

technical field [0001] The present invention relates to the field of sea state estimation (also known as sea state calculation, Sea Stateestimation) of ocean observation, especially relates to the use of image recognition method to carry out sea state calculation or sea state estimation, specifically, relates to the method of using the principal component analysis network in deep learning through Classify images of different ocean states to realize automatic recognition of ocean states. Background technique [0002] Sea state estimation (also known as sea state recognition or ocean state calculation), as an important part of ocean observation, has important strategic significance for marine environment and resource monitoring, sea area dynamic supervision, marine information management, marine target positioning and maritime safety. The current sea state estimation algorithm mainly uses the wave and wind speed data obtained by traditional navigation or satellite remote sensi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06N20/00
CPCG06N20/00G06F18/213G06F18/214
Inventor 张翠翠刘志磊常帅
Owner TIANJIN UNIV
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