Camera Defect Detection via Autocorrelation Noise Quantification

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Solution Overview

Problem

Cameras used in medical procedures exposed to radiation suffer from gradual damage, leading to adverse visual effects and potential misses in critical events during treatments, as existing methods require regular scheduled tests for defect detection.

Innovation Solution

A method and apparatus utilizing a processing unit with surface fit, subtraction, and peak quantification modules to detect camera defects by analyzing autocorrelation maps and quantifying noise in camera images, allowing for automatic and quantitative measurement of camera degradation without the need for regular tests.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If regular scheduled tests are performed to detect camera defects, then detection reliability is improved, but loss of time and productivity deteriorate due to operational interruptions

Engineering Contradiction:

Improvedefect detection reliabilityVSAvoidoperational interruption time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary defect detection by continuously analyzing autocorrelation maps during normal camera operation. The processing unit calculates autocorrelation maps from incoming video frames and detects defects before they affect critical monitoring functions, eliminating the need for scheduled operational interruptions.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The defect detection operates continuously in the background during normal camera operation. The processing unit continuously computes autocorrelation maps and monitors for defects without interrupting the camera's primary function of monitoring patient position and treatment areas, maintaining continuous useful action for both defect detection and patient monitoring.

Inventive Principle:

Principle #20Continuity of useful action

2Measurement precision

If manual inspection methods are used to detect camera defects, then device complexity is reduced, but measurement precision and detection capability deteriorate

Engineering Contradiction:

Improvedefect quantification precisionVSAvoidprocessing system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system replaces manual visual inspection with an automated digital processing system. The processing unit automatically computes autocorrelation maps from video frames and quantifies defect severity, substituting mechanical/manual inspection methods with computational analysis that provides superior measurement precision.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The camera system performs self-diagnosis by automatically analyzing its own output images for defects. The processing unit extracts features from the camera's video frames, computes autocorrelation maps, and quantifies defect severity without requiring external manual inspection, enabling the system to service itself.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS9773318B2Systems and methods for detecting camera defect caused by exposure to radiation

Publication Date: 2017.09.26 VARIAN MEDICAL SYSTEMS INC

AI summary

A method of detecting camera defect includes: obtaining an image by a processing unit, the processing unit having a surface fit module, a subtraction module, and a peak quantification module; determining a first autocorrelation map for a first sub-region in the image; determining, using the surface fit module, a first surface fit for first scene content in the first sub-region; subtracting, using the subtraction module, the first surface fit from the first autocorrelation map for the first sub-region in the image to obtain a first residual map; and quantifying, using the peak quantification module, a first noise in the first residual map.