Vehicle Image Distance Estimation Using Cyclic Pixel Frequency Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current distance estimation methods for autonomous driving technologies are limited in accuracy and reliability, particularly in complex environments, due to the reliance on traditional sensing devices like cameras and radar.
Innovation Solution
A distance estimation method that involves establishing a distance estimation region in an image captured by an image capturing device, applying image-processing tasks to extract cyclic variations in pixel feature parameters, and using frequency-analysis to calculate an intensity-frequency spectrum, thereby estimating the distance to a target object based on correspondence relationship information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional sensing devices like cameras and radar are used for distance estimation, then the system is simple and easy to implement, but the accuracy and reliability of distance estimation deteriorates in complex environments
Solution Approach 1:
The image capturing device divides the captured image into multiple distance estimation regions, and further segments each region into multiple pixel rows. This segmentation allows the system to process different regions with different strategies, improving measurement precision by focusing computational resources on critical areas while maintaining manageable system complexity.
Solution Approach 2:
The patent transforms the distance estimation problem from traditional 2D image space to a frequency domain analysis. By extracting cyclic variations in pixel feature parameters and applying frequency analysis, the system creates a new dimensional representation (intensity-frequency spectrum) that reveals distance information more clearly, thereby improving accuracy without proportionally increasing system complexity.
2Measurement precision
If advanced image processing and frequency analysis techniques are applied, then distance estimation accuracy improves, but computational complexity and processing time increase
Solution Approach 1:
The system applies different processing qualities to different regions: distance estimation regions receive intensive frequency analysis processing, while other regions use standard processing. Within distance estimation regions, only specific pixel rows containing cyclic variation patterns undergo complex analysis. This local quality approach maintains high accuracy in critical areas while preserving overall processing efficiency.
Solution Approach 2:
The patent applies frequency analysis selectively to extract cyclic variations in pixel feature parameters rather than processing all image data with the same intensity. By focusing computational effort on extracting specific cyclic patterns that correlate with distance, the system achieves high measurement precision without the excessive computational burden of exhaustive image processing.
3Reliability
If frequency analysis is applied to cyclic variations in pixel features, then reliability of distance estimation improves, but the complexity of the processing algorithm increases
Solution Approach 1:
The system extracts cyclic variations in pixel feature parameters from the image data, isolating the specific signal component that contains distance information. By taking out and analyzing only these cyclic variations through frequency analysis, rather than processing the entire image, the system improves reliability while keeping algorithm complexity manageable through focused processing.
Data Source
AI summary
A processor of a distance estimation apparatus executes distance estimation program instructions to accordingly (i) calculate, based on an image captured by an image capturing device mounted to a vehicle, information included in a cyclic variation in values of at least one pixel feature parameter included in selected pixels of the image, and (ii) estimate, based on the calculated information included in the cyclic variation, a distance from the vehicle to a target object related to the cyclic variation.