Object Identification Device Using Polarization and Brightness Switching
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Solution Overview
Problem
Conventional object identification devices face challenges in accurately identifying image regions of identification targets, such as road edges and traffic lanes, especially under varying brightness conditions, leading to potential false identifications and incorrect control operations, particularly when differential polarization degree methods fail due to low contrast imaging conditions.
Innovation Solution
An object identification device that uses an imaging unit to capture two polarization images, calculates brightness sum values and differential polarization degrees, and employs a selecting condition determination unit to switch between using differential polarization degree and brightness-based identification depending on imaging conditions, ensuring accurate identification by selecting the most appropriate image processing method for each scenario.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If differential polarization degree method is used for object identification, then identification accuracy is improved under normal imaging conditions, but identification accuracy deteriorates when imaging conditions result in low contrast
Solution Approach 1:
The system dynamically switches between two identification methods based on imaging conditions. A selecting condition determination unit evaluates whether the differential polarization degree method satisfies predetermined conditions, and if not, switches to using brightness sum values instead. This dynamic adaptation ensures reliable identification across varying lighting conditions.
Solution Approach 2:
The system changes the identification parameter based on imaging conditions. When the differential polarization degree does not satisfy the selecting condition (indicating low contrast conditions), the system switches to using brightness sum values as the identification parameter, thereby adapting to different imaging environments.
2Reliability
If brightness-based identification is used, then identification accuracy is maintained under low contrast conditions, but identification accuracy deteriorates under normal high contrast imaging conditions
Solution Approach 1:
The system dynamically selects which identification method to use based on real-time evaluation of imaging conditions. The selecting condition determination unit assesses whether the differential polarization degree method is suitable, and switches to brightness-based identification only when necessary, ensuring optimal performance across different conditions.
Solution Approach 2:
The system changes the identification parameter dynamically. Instead of using a fixed method, it switches between differential polarization degree and brightness sum values based on whether the imaging conditions satisfy predetermined selecting conditions, optimizing accuracy for each specific situation.
3Device complexity
If a single identification method is used for all conditions, then device complexity is reduced, but identification accuracy deteriorates under varying imaging conditions
Solution Approach 1:
The identification device performs multiple functions by incorporating both differential polarization degree method and brightness-based identification method. The selecting condition determination unit evaluates imaging conditions and selects the appropriate method, making the system universally applicable to various lighting conditions without requiring separate devices.
Solution Approach 2:
The system dynamically adapts its behavior based on imaging conditions. The selecting condition determination unit continuously evaluates whether the differential polarization degree method satisfies predetermined conditions, and switches methods accordingly, allowing a single device to optimize performance across varying conditions.
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
The device achieves higher accuracy in identifying image regions of identification targets even under difficult imaging conditions by dynamically selecting between differential polarization degree and brightness-based methods, thereby reducing false identifications and improving operational reliability.
Implementation Method 1
an imaging unit that receives two polarization lights included in reflected light from an object existing in the imaging region and having respective polarization directions different from each other, and that images respective polarization images
Data Source
AI summary
An object identification device identifying an image region of an identification target includes an imaging unit receiving two polarization lights and imaging respective polarization images, a brightness calculation unit dividing the two polarization images into processing regions and calculating a brightness sum value between the two polarizations images for each processing region, a differential polarization degree calculation unit calculating a differential polarization degree for each processing region, a selecting condition determination unit determining whether the differential polarization degree satisfies a predetermined selecting condition, and an object identification processing unit specifying the processing region based on the differential polarization degree or the brightness sum value depending on whether the predetermined selecting condition is satisfied and identifying plural processing regions that are specified as the processing regions as the image region of the identification target.