Signal Processing System for Spectral Identification Using Dedicated Base Vectors
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Solution Overview
Problem
Current signal processing systems for identifying subjects with specific spectral characteristics, such as blood vessels, face challenges in accurately distinguishing between spectral characteristics and noise, leading to unreliable identification results.
Innovation Solution
A signal processing system comprising a base vector acquisition unit, a system spectral characteristic acquisition unit, a calculation unit, and an output signal calculation unit, which utilize dedicated base vectors and spectral characteristics of imaging systems to calculate weighting factors for identifying subjects, thereby reducing noise influence and improving reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If broadband light is used for image acquisition, then more spectral information is obtained, but noise and interference increase making it difficult to identify specific spectral characteristics
Solution Approach 1:
The patent extracts only the relevant spectral information corresponding to the identification target from the broadband spectral data. By using the obtained spectral characteristic and comparing it with stored spectral characteristics of targets, the system extracts and processes only the necessary spectral components, discarding noise and irrelevant information, thus resolving the contradiction between obtaining comprehensive spectral information and ensuring reliable identification.
Solution Approach 2:
The patent transforms the broadband spectral data by changing its parameters through comparison with stored spectral characteristics. The system converts the raw spectral information into a form that highlights the specific spectral features of the identification target, effectively separating signal from noise through parameter transformation and pattern matching.
2Measurement precision
If spectral processing is performed to identify specific subjects, then identification accuracy improves, but processing complexity increases
Solution Approach 1:
The patent performs preliminary actions by pre-storing spectral characteristics of various identification targets before actual image acquisition. This preprocessing step creates a reference database that simplifies the subsequent identification process, allowing the system to achieve high accuracy through direct comparison rather than complex real-time spectral analysis.
Solution Approach 2:
The patent uses copying by storing reference spectral characteristic data in advance and comparing it with the acquired spectral data. Instead of performing complex spectral decomposition and analysis during real-time processing, the system copies pre-analyzed spectral signatures and matches them against the current image data, significantly reducing processing complexity while maintaining high identification accuracy.
Data Source
AI summary
A dedicated base vector based on a known spectral characteristic of a subject as an identification target having the known spectral characteristic and a spectral characteristic of an imaging system, which includes a spectral characteristic concerning a color imaging system used for image acquisition of subjects including the subject as the identification target and a spectral characteristic concerning illumination light used when image acquisition of the subjects by the color imaging system, are acquired. A weighting factor concerning the dedicated base vector is calculated based on an image signal obtained by image acquisition of the subject by the color imaging system, the dedicated has vector, and the spectral characteristic of the imaging system. An identification result of the subject which is the identification target having the known spectral characteristic is calculated based on the weighting factor concerning the dedicated base vector to output as an output signal.