Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Methods And Systems For Automatic Object Detection From Aerial Imagery

An aerial image and image technology, applied in the field of objects in aerial images, can solve problems such as increasing computational complexity, limiting application feasibility and efficiency, etc.

Active Publication Date: 2018-06-12
GEOSAT AEROSPACE & TECH
View PDF3 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Increasing the resolution of aerial images may help to improve the accuracy of object detection, however, at the same time, performing object recognition and detection on high-resolution images will increase computational complexity, which limits the feasibility of specific applications sex and efficiency

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
  • Methods And Systems For Automatic Object Detection From Aerial Imagery
  • Methods And Systems For Automatic Object Detection From Aerial Imagery
  • Methods And Systems For Automatic Object Detection From Aerial Imagery

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0022] The present invention generally relates to methods and systems for detecting objects in aerial images. The intended target object may be a plant, tree, oil palm, object, building, facility, land, feature, or any combination thereof. Generally speaking, the target object to be detected can include anything, such as objects, buildings, facilities, plants, trees, animals, and even human beings. Target objects can have many characteristics in color, shape and / or appearance, and these characteristics of the target object can be used to detect the target object in the image in the region of interest.

[0023] figure 1 is a schematic illustration of an example aerial image of an area for automatic object detection according to disclosed embodiments. For example, oil palm trees are example target objects to be detected in aerial images of the area, and these oil palm trees have a specific height above the ground. In some embodiments, the disclosed method and system may inclu...

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

Methods and systems for detecting objects from aerial imagery are disclosed. According to certain embodiments, the method may include obtaining a Digital Surface Model (DSM) image of an area. The method may also include obtaining a DSM image of one or more target objects. The method may further include detecting the target object in the area based on the DSM images of the area and the one or moretarget objects. The method may further include recognizing the detected target objects by artificial intelligence. The method may further include acquiring the positions of the recognized target objects. The method may further include calculating the number of the recognized target objects.

Description

technical field [0001] The present invention generally relates to a method and system for detecting objects in an aerial image, and in particular, relates to template matching using artificial intelligence technology to detect and identify an aerial image of an area of ​​interest (anaerial image of an area of ​​interest). methods and systems for objects within interest). Background technique [0002] Automatic object detection is very useful for finding and identifying objects of interest within an image. Although humans can recognize one or a few objects in an image with a little effort, it is challenging for humans to find and recognize a large number of objects in an image. When the target object in the image is displayed at different sizes and ratios, or even in different rotation angles, it will look different from different viewpoints. Certain computer-implemented methods can detect target objects based on appearance or characteristics, however, for some applications...

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): G06K9/00G06K9/62G06V10/25G06V10/56G06V10/75G06V10/764
CPCG06V20/13G06V20/40G06F18/214G06F18/241G06T2207/10028G06T2207/20084G06T2207/30188G06T7/73G06T7/74G01C11/02G06T2207/10032G06T2207/20081G06T2207/30242G06V20/188G06V10/25G06V10/56G06V10/462G06V10/75G06V10/764G06F18/22G06F18/24
Inventor 罗正方陈姿秀柯长荣吴俊毅
Owner GEOSAT AEROSPACE & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
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