Camera Occlusion Detection via Spectral Intensity Analysis
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Solution Overview
Problem
Current methods fail to effectively detect near-field occlusions in camera images, leading to corrupted images and downstream processing failures in applications like autonomous vehicles and facial recognition.
Innovation Solution
A method involving a color camera that captures images, analyzes electromagnetic radiation intensity across the spectrum by comparing intensity in one frequency band to others, and identifies occlusions by counting pixel bins, tagging images with occlusion indicators when similarity thresholds are exceeded.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional image capture methods are used without occlusion detection, then image capture speed is maintained, but image quality and reliability deteriorate due to undetected occlusions corrupting the images
Solution Approach 1:
The image sensor is divided into multiple frequency bands (e.g., red, green, blue channels) that are analyzed independently. Each frequency band's intensity is compared to detect occlusions, allowing parallel processing that maintains speed while improving reliability through multi-channel analysis
Solution Approach 2:
The system performs preliminary analysis of electromagnetic radiation intensity across frequency bands before final image processing. By detecting occlusions in the frequency domain early in the pipeline, the system can tag or discard corrupted images before they reach downstream processing stages, ensuring reliability without bottlenecking capture speed
2Measurement precision
If electromagnetic radiation intensity analysis across frequency bands is performed, then occlusion detection accuracy is improved, but computational complexity increases
Solution Approach 1:
The system transforms the image data from spatial domain to frequency domain representation, analyzing intensity parameters across different frequency bands. By changing the parameter space from pixel intensities to spectral intensities, the system achieves more accurate occlusion detection through characteristic spectral signatures while using efficient Fourier transform algorithms to manage computational complexity
Solution Approach 2:
The patent creates simplified spectral profiles or histograms representing the intensity distribution across frequency bands. These compressed representations serve as copies of the full spectral data, enabling accurate occlusion detection through comparison of simplified models rather than exhaustive analysis of all frequency components, thereby reducing computational complexity
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
This approach accurately detects occlusions, ensuring clean images are processed correctly and reducing failures in software applications reliant on image input.
Implementation Method 1
capturing an image of a scene using the camera; analyzing intensity of electromagnetic radiation forming the at least one image
Implementation Method 2
detecting an occlusion on a lens of the camera based on variation of intensity of the electromagnetic radiation across the electromagnetic spectrum
Data Source
AI summary
A method is presented for detecting occlusions on a color camera. The method includes: capturing an image of a scene using the camera; analyzing intensity of electromagnetic radiation forming the at least one image, where the intensity of the electromagnetic radiation is analyzed across the electromagnetic spectrum; detecting an occlusion on a lens of the camera based on variation of intensity of the electromagnetic radiation across the electromagnetic spectrum; and tagging the image with an indicator of the occlusion, where the tagging occurs in response to detecting an occlusion on the camera.