Shadow Removal via Color Ratio Invariance for Road Detection
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Solution Overview
Problem
Existing shadow removal methods in machine vision, particularly for color images, fail to effectively remove shadows in real-time, especially in strong shadow situations, impacting road detection in intelligent vehicle perception technology.
Innovation Solution
A shadow removal method involving shadow-free feature analysis, transformation parameter acquisition, and shadow-free feature imaging, which converts RGB values into a shadow-free feature matrix using a linear relation between color components, allowing for effective shadow removal and subsequent image processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If shadow detection and removal method is used to detect shadow region and repair it using restoration algorithm, then shadow removal effect is improved, but processing complexity increases and processing speed decreases
Solution Approach 1:
The patent extracts only the necessary shadow-free features (color ratio relationships) from the image data, rather than performing full shadow detection and restoration. By extracting the invariant color ratio feature that remains consistent under shadow illumination, the method achieves shadow removal without complex restoration algorithms, thus maintaining high processing speed while effectively removing shadows
Solution Approach 2:
The patent replaces the mechanical shadow restoration process with a mathematical transformation based on color space conversion. Instead of detecting shadows and manually restoring them, the method uses color ratio relationships in RGB or HSV spaces to directly compute shadow-free image values through algebraic operations, significantly simplifying the processing pipeline
2Object-affected harmful factors
If anti-shadow feature extractor is used to extract brightness and color components through color space conversion, then shadow interference is reduced to some extent, but shadows in strong shadow situations cannot be completely removed
Solution Approach 1:
The patent changes the parameter used for shadow removal from simple brightness or color components to the ratio relationship between color components. By using ratios such as R/G, B/G, or H/S in HSV space, the method captures illumination-invariant features that remain constant even under strong shadow conditions, thereby achieving complete shadow removal where traditional extractors fail
3Device complexity
If grayscale component composed of weighted sum of RGB components is used for processing, then processing is simplified, but illumination changes and shadow interference still affect the results
Solution Approach 1:
Instead of using a single grayscale component (one-dimensional representation), the patent utilizes the ratio relationships between multiple color components, effectively adding dimensional information. The ratio features preserve relative color information that is invariant to illumination changes, providing a more robust representation that maintains simplicity while resisting shadow interference
Data Source
AI summary
Disclosed are a shadow removing method for an image and an application. The shadow removing method comprises a shadow-free feature analysis process, a shadow-free transformation parameter acquisition process and a shadow-free feature imaging process. The application is for road surface detection, a detection method comprising: firstly, using a shadow-free feature extraction method to select a region of interest and extract a feature; next, performing image filtering, segmentation and road surface region selection; lastly, performing image morphology filtering and hole filling. The method may remove shadows in color images, thus serving as a pre-processing step applied in various machine vision fields, and the application in road surface detection may solve the problem of detecting a road surface in dark shadows. The method has the advantages of having low complexity, high processing speed and high accuracy.