Hyperspectral and Depth Imaging for Agricultural Infestation Detection
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Solution Overview
Problem
Current methods for detecting infestation in agricultural products are inaccurate and destructive, often failing to detect internal infestations, leading to the potential spread of infestation to other products and the cancellation of entire batches due to incomplete inspection.
Innovation Solution
A system and method that combines hyperspectral imaging and depth imaging data to derive spectral signatures and morphological details, providing a 360° view of agricultural products, and classifies regions based on pre-defined signatures to detect infestation, using a transformation function to correct for spectral losses and utilizing X-ray data for internal inspections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual inspection and sample-based laboratory analysis are used, then manual handling and sampling is required, but this affects product quality and causes permanent destruction of product samples
Solution Approach 1:
The patent replaces manual visual inspection and physical sampling with hyperspectral imaging technology. The system uses spectral signatures captured through non-contact imaging to detect infestations, eliminating the need for manual handling and destructive sampling while maintaining high detection accuracy.
Solution Approach 2:
The patent creates spectral copies of the agricultural products through hyperspectral imaging. Instead of physically sampling the product, the system captures spectral data that represents the product's condition, allowing analysis without destroying the original product.
2Object-affected harmful factors
If non-destructive techniques such as RGB camera based image analysis and Hyperspectral Imaging are used, then product quality is preserved, but infestation in inner regions remains undetected
Solution Approach 1:
The patent transitions from two-dimensional surface imaging to three-dimensional volumetric analysis by integrating hyperspectral imaging with depth information. This dimensional expansion enables detection of infestations within the internal structure of products while maintaining non-destructive inspection.
Solution Approach 2:
The patent embeds multiple detection capabilities within a unified system. The hyperspectral imaging system is integrated with depth sensing and spectral analysis components, creating a nested architecture where multiple detection dimensions work together to reveal internal infestations that would be invisible to surface-level inspection alone.
3Productivity
If sample-based analysis is used, then inspection can be performed, but results are not fool-proof and cause permanent destruction of product samples
Solution Approach 1:
The patent performs comprehensive spectral capture and analysis on the entire product surface before any decision is made. By capturing complete spectral signatures across the whole product rather than sampling, the system ensures reliable detection results are obtained in advance, eliminating the need for destructive sampling and ensuring accurate batch assessment.
4Measurement precision
If thorough inspection of all products is performed, then detection accuracy improves, but inspection time and complexity increase
Solution Approach 1:
The patent implements continuous spectral capture across the entire product surface without interruption. The hyperspectral imaging system moves continuously through the product, capturing spectral data at every point along the inspection path, ensuring complete and thorough detection while maintaining efficient throughput through automated continuous operation.
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
Enables accurate, non-destructive detection of infestations, ensuring the quality and safety of agricultural products by providing a comprehensive analysis that reduces false negatives and batch cancellations, allowing for timely segregation of good and bad products.
Implementation Method 1
capturing imaging data for a plurality of points on an agricultural product upon directing a light source at the plurality of points on the agricultural product
Data Source
AI summary
System and method of detecting infestation in agricultural products is disclosed. In one embodiment, an infestation detection system captures hyperspectral imaging data and depth imaging data for a plurality of points on an agricultural product upon directing a light source at the agricultural product. The system analyses the captured imaging data to derive morphological details as well as spectral signatures for complete 360° view of the plurality of points on the agricultural product. In an embodiment, the spectral signatures may be corrected for one or more pixels associated with the plurality of points in the agricultural product by integrating the hyperspectral imaging data with the depth imaging data. The system further classifies one or more regions of the agricultural product based on matching of spectral signatures for the one or more pixels with pre-defined spectral signatures stored for a plurality of agricultural products, and accordingly detect infestation.