3D LiDAR Region of Interest Scanning for Depth Resolution
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Solution Overview
Problem
Existing 3D image scanning systems face challenges with low recognition of objects under varying lighting conditions and reduced depth information resolution at increased distances or field of view, particularly due to susceptibility to surrounding light sources and limitations in current depth sensors.
Innovation Solution
An image scanning system comprising a first optical device, a second optical device (such as a 3D LiDAR sensor), and a processing unit that detects objects, calculates relative coordinates, and controls the second optical device to continuously scan regions of interest, generating high-resolution depth image information which is then integrated into the image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If depth sensors based on camera images (stereo camera or structured light) are used, then 3D depth information can be obtained, but the resolution is reduced as distance or field of view increases and recognition is poor under varying lighting conditions
Solution Approach 1:
The system dynamically adjusts the scanning strategy based on detected objects. The control module continuously scans regions of interest by adjusting the scanning parameters (such as scanning angle and frequency) according to the relative coordinates of detected objects, enabling the system to adapt to different distances and lighting conditions while maintaining high depth information resolution
Solution Approach 2:
The system applies different scanning resolutions to different regions of the image. Regions of interest (detected objects) receive continuous high-resolution scanning, while other areas use standard scanning. This local quality differentiation allows high measurement precision for objects without sacrificing overall system adaptability
2Measurement precision
If continuous scanning of regions of interest is performed to improve depth information resolution, then scanning speed and accuracy increase, but system complexity increases
Solution Approach 1:
The system segments the scanning process into two distinct modes: continuous scanning for regions of interest (detected objects) and standard scanning for other areas. This segmentation allows high measurement precision for objects while keeping the overall system complexity manageable by applying complex control only where necessary
Solution Approach 2:
The system performs preliminary object detection using the object detection module before initiating continuous scanning. By detecting objects first and calculating their relative coordinates, the system prepares the scanning strategy in advance, which simplifies the control logic during the actual scanning process
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the resolution and accuracy of depth image information, leading to improved object recognition and more precise detection in diverse environments, overcoming limitations of prior art by increasing scanning resolution and speed.
Implementation Method 1
a second optical device (such as a 3D LiDAR sensor)... allowing the processing unit to generate depth image information
Data Source
AI summary
The present disclosure provides an image scanning system and an image scanning method. The image scanning method includes: receiving a first image of a first optical device and a second image of a second optical device; determining objects of the first image or the second image; selecting at least one of the objects of the first image or the second image as a region of interest to scan the region of interest continuously by the second optical device so as to obtain depth image information of the region of interest; and integrating the depth image information into the first or second image. Therefore, the present disclosure obtains higher image resolutions, faster scanning speeds and more accurate recognition results.