Unlock instant, AI-driven research and patent intelligence for your innovation.

Satellite image road segmentation method and system based on deep learning

A satellite image and deep learning technology, applied in the field of image processing to enhance data, avoid network overfitting, and improve accuracy and efficiency

Pending Publication Date: 2020-12-04
HAINAN UNIVERSITY
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a satellite image road segmentation method and system based on deep learning to overcome or at least partially solve the above-mentioned problems existing in the existing road image segmentation algorithm

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Satellite image road segmentation method and system based on deep learning
  • Satellite image road segmentation method and system based on deep learning
  • Satellite image road segmentation method and system based on deep learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0042] The principles and features of the present invention will be described below in conjunction with the accompanying drawings, and the enumerated embodiments are only used to explain the present invention, and are not intended to limit the scope of the present invention.

[0043] refer to figure 1 , the present invention provides a satellite image road segmentation method based on deep learning, the method comprising:

[0044] The first satellite road image is obtained, the first satellite road image is preprocessed, the satellite road automatic segmentation model is established, and the first satellite road image is input into the satellite road automatic segmentation model for training.

[0045] The second satellite road image is obtained, the second satellite road image is preprocessed, the second satellite road image is input into the satellite road automatic segmentation model to segment road elements, and the segmentation result is output.

[0046] In some embodimen...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides a satellite image road segmentation method and system based on deep learning. The method comprises the steps of: obtaining a first satellite road image, carrying out preprocessing on the first satellite road image, building a satellite road automatic segmentation model, and inputting the first satellite road image into the satellite road automatic segmentation model for training; and acquiring a second satellite road image, preprocessing the second satellite road image, inputting the second satellite road image into the satellite road automatic segmentation model to segment road elements, and outputting a segmentation result. According to the method, the images are preprocessed to enhance the data, so that the network over-fitting phenomenon is avoided; the satelliteroad image is automatically segmented based on the deep learning technology, and the accuracy and efficiency of road element segmentation are effectively improved.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a satellite image road segmentation method and system based on deep learning. Background technique [0002] Roads are an important factor affecting autonomous driving technology. The accuracy of roads affects the accuracy of maps. However, due to the rapid development of society, the frequency of road planning is getting faster and faster. The current ways to obtain roads are: (1) Use vehicle-mounted laser scanning equipment to obtain road surface information through traversal scanning, but it consumes a lot of manpower and material resources. (2) Using aerial or satellite images to obtain road information through technical methods, this method can relatively save a lot of manpower and time. [0003] In recent years, with the development of computer hardware and the gradual improvement of computing power, deep learning has achieved significant results in the fie...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06T7/10G06N3/04G06N3/08
CPCG06T7/10G06N3/08G06T2207/10032G06T2207/20081G06T2207/20084G06T2207/30204G06T2207/30256G06N3/045
Inventor 黄梦醒张新华张雨冯思玲冯文龙吴迪
Owner HAINAN UNIVERSITY