Camera Tampering Detection via Edge Image Similarity
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Solution Overview
Problem
Existing camera tampering detection methods require significant memory and processing capacity, making them inefficient and resource-intensive, and are sensitive to vibrations and minor movements, which complicates the identification of genuine tampering events.
Innovation Solution
A method that converts images into edge images, generates a similarity value to detect tampering by comparing with a reference edge image, updates the reference image only when consecutive frames indicate no tampering, and uses counters to confirm tampering events before triggering an alarm, reducing memory and processing needs while stabilizing the detection process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional dysfunction detection methods are used to detect camera tampering, then detection capability is provided, but memory usage and processing capacity requirements increase significantly
Solution Approach 1:
The patent extracts only the essential edge information from complete image frames by converting images to edge images. This extraction principle allows the system to detect camera tampering by analyzing only the edge structures rather than processing entire high-resolution frames, significantly reducing memory requirements while maintaining detection effectiveness
Solution Approach 2:
The patent applies local quality by focusing computational resources on edge regions of images rather than uniform processing of all pixels. By converting to edge images and comparing only edge features, the system achieves tampering detection with reduced data volumes, addressing the memory constraint while preserving critical detection information
2Reliability
If traditional dysfunction detection methods are used to detect camera tampering, then detection capability is provided, but processing capacity requirements increase significantly
Solution Approach 1:
The patent extracts only the essential edge information from complete image frames by converting images to edge images. This extraction principle allows the system to detect camera tampering by analyzing only the edge structures rather than processing entire high-resolution frames, significantly reducing memory requirements while maintaining detection effectiveness
Solution Approach 2:
The patent applies local quality by focusing computational resources on edge regions of images rather than uniform processing of all pixels. By converting to edge images and comparing only edge features, the system achieves tampering detection with reduced data volumes, addressing the memory constraint while preserving critical detection information
3Measurement precision
If frame-by-frame analysis is used to detect camera tampering, then detection accuracy is improved, but sensitivity to vibrations and minor movements increases
Solution Approach 1:
The patent applies preliminary action by establishing a reference edge image from initial frames before actual tampering detection begins. This reference serves as a stable baseline that accounts for normal environmental variations and vibrations, allowing subsequent comparisons to focus on genuine tampering events rather than normal operational fluctuations
Solution Approach 2:
The patent changes the analysis parameter from complete image frames to edge images only. This parameter transformation reduces sensitivity to vibrations and minor movements because edge structures are more stable and less affected by small positional variations, while still maintaining the ability to detect significant tampering events
4Adaptability or versatility
If reference edge image is updated frequently to adapt to scene changes, then adaptability to environment changes is improved, but false tampering indications increase
Solution Approach 1:
The patent applies preliminary action by establishing a reference edge image from initial frames before actual tampering detection begins. This reference serves as a stable baseline that accounts for normal environmental variations and vibrations, allowing subsequent comparisons to focus on genuine tampering events rather than normal operational fluctuations
Solution Approach 2:
The patent changes the analysis parameter from complete image frames to edge images only. This parameter transformation reduces sensitivity to vibrations and minor movements because edge structures are more stable and less affected by small positional variations, while still maintaining the ability to detect significant tampering events
Data Source
AI summary
A method and a module for identifying possible tampering of a camera view. The method comprising receiving an image for analysis from an image sequence, converting the received image into an edge image, generating a similarity value indicating a level of similarity between said edge image and a reference edge image, indicating possible tampering of the camera view if the similarity value is within a specified tampering range, and updating the reference edge image by combining a recently analyzed edge image with the reference edge image in case of each one of a predetermined number of consecutively analyzed images does not result in an indication of possible tampering.