Cartesian Camera Arm for Stable Hyperspectral Fruit Imaging
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Solution Overview
Problem
Existing systems for determining characteristics of food products, such as vegetables and fruit, using hyperspectral imaging face challenges due to variable natural light spectra, which can cause errors in image processing and analysis, and often fail to isolate the desired portion of the fruit-bearing plant for verification and additional processing using AI models.
Innovation Solution
A mobile camera system with a cartesian arm capable of moving a hyperspectral camera along three axes, accompanied by an RGB camera and a controlled light source, allowing for precise image capture and illumination, enabling accurate hyperspectral image acquisition and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If hyperspectral imaging is performed using natural light, then the system can operate without additional illumination equipment, but the variable spectra of natural light cause errors in image processing and analysis
Solution Approach 1:
The patent introduces a controlled light source as an intermediary between the object being imaged and the hyperspectral camera. This light source provides stable, controllable illumination that mediates the imaging process, eliminating the variability of natural light while maintaining system functionality.
Solution Approach 2:
The patent changes the illumination parameter from uncontrolled natural light to controlled artificial light with specific spectral characteristics. This parameter change allows for consistent, repeatable measurements by controlling the spectral content and intensity of the illumination.
2Productivity
If only hyperspectral images are captured, then the system can focus on spectral analysis, but it becomes difficult to isolate the desired portion of the fruit-bearing plant for verification and AI processing
Solution Approach 1:
The patent merges multiple imaging modalities (hyperspectral imaging, RGB imaging, and depth imaging) into a single integrated system. This combination allows the system to capture both spectral information and spatial context simultaneously, enabling accurate isolation and verification of target regions.
Solution Approach 2:
The patent adds spatial and visual dimensions to the spectral data by incorporating RGB and depth cameras. This multi-dimensional approach allows for better localization and verification of the regions being analyzed in the hyperspectral images.
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 system provides reliable and accurate hyperspectral image data for analyzing food product characteristics, reducing errors caused by variable light spectra and allowing for effective AI model-based processing and verification.
Implementation Method 1
a light source that is able to provide illumination while the second camera generates the second image data. The light source can emit a predetermined spectrum of light. The predetermined spectrum of light can be a range of about 400 nm to about 1000 nm.
Data Source
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AI summary
A mobile camera apparatus includes a cartesian arm that is able to move along three axes, a first camera (162) to generate first image data, and a second camera (163) to generate second image data and is attached to the cartesian arm. The cartesian arm is operable to move the second camera (163) along the three axes, and the second image data includes hyperspectral image data.