Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A City Ortho-Segmentation Recognition Method Based on Multi-window State Recognition Process

A recognition process, segmentation recognition technology, applied in the field of image processing, can solve problems such as poor recognition

Active Publication Date: 2022-08-02
埃洛克航空科技(北京)有限公司
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The main purpose of the present invention is to provide an urban orthographic segmentation recognition method based on the multi-window recognition process, so as to solve the problem that the entities in the edge area of ​​the urban orthophoto image cannot be well recognized

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

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0023] An urban orthophoto segmentation and identification method based on a multi-window state identification process includes the following steps: the first step is to initialize the sliding window size and step size, and to perform sliding segmentation on the urban orthoimage map; the second step, the window image recognition, the third step. In three steps, the window moves, and the second step is repeated until the recognition is completed.

[0024] The sliding window method is used to perform sliding segmentation on the urban orthophoto image. In this process, the size of the sliding window and the step size of each sliding will directly affect the quality and efficiency of recognition. If the sliding step size is too small, a large number of Overlapping images, thereby increasing a large number of repeated calculations, will greatly reduce the performance of the entire system; at the same time, if the sliding window is too large or too small, it will also affect the fina...

Embodiment 2

[0032] An urban orthophoto segmentation and identification method based on a multi-window state identification process includes the following steps: the first step is to initialize the sliding window size and step size, and to perform sliding segmentation on the urban orthoimage map; the second step, the window image recognition, the third step. In three steps, the window moves, and the second step is repeated until the recognition is completed.

[0033] The sliding window method is used to perform sliding segmentation on the urban orthophoto image. In this process, the size of the sliding window and the step size of each sliding will directly affect the quality and efficiency of recognition. If the sliding step size is too small, a large number of Overlapping images, thereby increasing a large number of repeated calculations, will greatly reduce the performance of the entire system; at the same time, if the sliding window is too large or too small, it will also affect the fina...

Embodiment 3

[0041] An urban orthophoto segmentation and identification method based on a multi-window state identification process includes the following steps: the first step is to initialize the sliding window size and step size, and to perform sliding segmentation on the urban orthoimage map; the second step, the window image recognition, the third step. In three steps, the window moves, and the second step is repeated until the recognition is completed.

[0042]The sliding window method is used to perform sliding segmentation on the urban orthophoto image. In this process, the size of the sliding window and the step size of each sliding will directly affect the quality and efficiency of recognition. If the sliding step size is too small, a large number of Overlapping images, thereby increasing a large number of repeated calculations, will greatly reduce the performance of the entire system; at the same time, if the sliding window is too large or too small, it will also affect the final...

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 discloses an urban orthophoto segmentation identification method device and electronic equipment based on a multi-window state identification process. The method includes the following steps. The first step is to initialize the sliding window size and step size, and perform sliding segmentation on the urban orthophoto image. , the second step, window image recognition, the third step, the window moving, and repeat the second step until the recognition is completed. The embodiment of the present invention can well identify the edge area affected by the urban orthophoto.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an urban orthophoto segmentation and identification method based on a multi-window state identification process. Background technique [0002] At present, the urban orthophoto map is very huge and contains a lot of information. The existing recognition algorithm cannot directly identify and process the complete orthophoto map of a city, so it needs to be cut and re-identified. The current direct cutting method has a The serious problem is that cutting produces a large number of edge areas, which leads to the fact that the entities in the edge areas cannot be well recognized, thus the overall recognition effect is imaged. [0003] The Chinese invention patent with the application number CN201810803413.1 discloses a deep learning-based remote sensing automatic identification method and device for petroleum facilities. The method includes: converting the remote sensing data...

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
Patent Type & Authority Patents(China)
IPC IPC(8): G06V20/10G06V10/26
CPCG06V20/00G06V10/267
Inventor 由清圳
Owner 埃洛克航空科技(北京)有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com