Hyperspectral Camera N-Band Optimization for Material Distinction
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Solution Overview
Problem
Existing image processing technologies face challenges in accurately distinguishing between shadows and material object edges due to indistinguishable color values under different illumination conditions, leading to false positives or negatives in image analysis.
Innovation Solution
A method and system that optimize image recording by selecting N color bands based on experimentation to minimize spectral mimics, using a hyperspectral camera to record images in multiple bands, and employing a metric to quantify undesirable conditions, thereby improving the separation of illumination and material components in images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If RGB color bands are used for image recording, then the image can be displayed in aesthetically pleasing colors, but different materials under different illumination conditions become indistinguishable
Solution Approach 1:
The patent segments the continuous spectrum into N discrete color bands for image recording. Instead of using only three broad RGB bands, the image is divided into multiple spectral segments that capture different portions of the spectrum. This segmentation allows the system to distinguish between materials under different illumination by analyzing their spectral signatures across multiple bands, thereby resolving the indistinguishability problem while maintaining manufacturing feasibility.
Solution Approach 2:
The patent transitions from three-dimensional RGB color space to an N-dimensional spectral space by recording images in N color bands. This dimensional expansion provides additional information about the spectral characteristics of materials, enabling better distinction between materials under different illumination conditions. The extra dimensions in spectral space allow for more robust material identification beyond what is possible with standard RGB imaging.
2Device complexity
If standard RGB cameras are used, then the system remains simple and widely compatible, but spectral mimics cause false positives or negatives in image analysis
Solution Approach 1:
The patent changes the spectral parameters of the imaging system by selecting N specific color bands with optimized wavelengths, bandwidths, and relative positions. This parameter optimization is performed to minimize the occurrence of spectral mimics - cases where different materials appear identical in RGB but differ in their spectral characteristics. By carefully selecting and optimizing these spectral parameters, the system achieves higher reliability in image analysis while maintaining relative system simplicity and compatibility.
Data Source
AI summary
In a first exemplary embodiment of the present invention, a camera is provided. The camera comprises a lens and a sensor to record an image focused by the lens in N color bands, wherein N equals a number of color bands, with the number and respective locations and widths of the N color bands being selected to optimize the image for processing.