Vehicle Camera Color Correction for Recognition Accuracy
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Solution Overview
Problem
Image processing apparatuses in vehicles face challenges in accurately recognizing preceding or oncoming vehicles due to variations in color characteristics caused by components like windshields, lenses, and aging of image pickup elements, leading to incorrect recognition.
Innovation Solution
An image processing apparatus with a correction unit that updates pixel values using correction coefficients to match standard color characteristics, ensuring accurate recognition by comparing acquired color characteristics with stored standards and adjusting coefficients to minimize differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If image data is acquired using a camera with components like windshield, lens, and image pickup element, then image recognition can be performed, but color characteristics vary due to component characteristics and aging, leading to incorrect recognition
Solution Approach 1:
The patent applies preliminary action by pre-storing standard color characteristics of recognition targets (such as vehicle colors) in the storage unit before actual image recognition occurs. When image data is acquired, the system compares the acquired color characteristics against these pre-stored standards to determine if correction is needed, enabling accurate recognition despite component variations and aging effects.
Solution Approach 2:
The patent implements feedback by continuously comparing the color characteristics of acquired image data with stored standard color characteristics, and using this comparison result to update correction coefficients. This closed-loop feedback mechanism ensures that the system adapts to component aging and maintains accurate color representation over time, directly addressing the reliability-precision contradiction.
2Measurement precision
If correction coefficients are updated frequently to maintain color accuracy, then recognition precision improves, but system complexity and processing time increase
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting correction coefficients based on the comparison between acquired and standard color characteristics. Instead of redesigning the entire system, the invention modifies specific parameters (correction coefficients) to compensate for component variations and aging, thereby improving measurement precision without significantly increasing device complexity.
Solution Approach 2:
The system performs self-service by automatically updating its own correction coefficients through the comparison and update process. The image processing apparatus uses its own acquired image data and stored standards to self-correct color inaccuracies, eliminating the need for external calibration equipment or complex manual adjustment mechanisms, thus improving precision while maintaining simple system architecture.
Data Source
AI summary
In an image processing apparatus, an image acquisition unit acquires an image. A correction unit corrects pixel values of pixels composed of the acquired image by using correction coefficients to produce a correct image. An object recognition unit recognizes an object in the corrected image. A storage unit stores in advance standard color characteristics of a predetermined object which is a recognition target. A color characteristics acquisition unit acquires color characteristics of the predetermined object if the predetermined object is recognized by the object recognition unit. A comparison unit compares the color characteristics of the acquired object with the standard color characteristics of the same predetermined object stored in advance in the storage unit. An updating unit updates the correction coefficients used in the correction unit based on a result of comparison so as to reduce a difference between the color characteristics and the standard color characteristics.