Illumination Invariant Road Marking Detection
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Solution Overview
Problem
Current computer vision systems for automotive driver-assistance devices face challenges in accurately identifying painted road markings due to variations in illumination, which affect the accuracy of image processing and analysis.
Innovation Solution
A method and system that transform image pixels from RGB color space to log color space, generate a log chromaticity plane, and orient it based on a bi-illuminant dichromatic reflection model to create an illumination-invariant representation of road images, allowing for accurate identification of road markings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard RGB color space processing is used for road image analysis, then the processing is simple and fast, but the accuracy of road marking identification deteriorates under varying illumination conditions
Solution Approach 1:
The patent transforms image processing from standard RGB color space to log color space, changing the parameter representation of color values. This transformation allows the system to achieve illumination invariance by operating in a different mathematical space where lighting variations have reduced impact on material color identification, thereby improving road marking detection accuracy without requiring complex additional hardware
Solution Approach 2:
The patent introduces a log chromaticity plane as an intermediary representation between the raw RGB image and the final road marking identification. This intermediate step transforms the color information into a format that separates material properties from illumination effects, serving as a mediator that improves measurement precision while managing processing complexity through structured transformation
2Reliability
If illumination-invariant processing is implemented to separate material properties from lighting effects, then the reliability of image analysis improves, but the computational complexity increases
Solution Approach 1:
By changing the color space parameters from linear RGB to logarithmic color space, the system achieves illumination invariance through mathematical transformation rather than complex physical modeling. This parameter change approach maintains reliability by preserving the essential color information while removing illumination dependencies, and manages complexity by using well-established color space transformation techniques
Solution Approach 2:
The patent projects three-dimensional log color space values onto a two-dimensional log chromaticity plane, changing the dimensionality of the data representation. This dimensional reduction simplifies the processing by eliminating the intensity dimension that carries illumination information, thereby improving reliability for material identification while reducing the complexity of subsequent analysis operations
Data Source
AI summary
An automated, computerized method is provided for processing an image. The method includes the steps of arranging a digital camera on a vehicle body, operating the digital camera to provide an image file depicting an image of a scene related to vehicle operation on a road, in a computer memory, receiving from the memory the image file depicting pixels of an image of the scene related to vehicle operation on a road, and using an analysis of the pixels to generate an illumination invariant image of the scene. The illumination-invariant image is converted to a grayscale image and the grayscale image is then converted to an illumination-invariant color image.