Automated Moving Object Detection via Image Raster Comparison
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Solution Overview
Problem
Moving object detection and tracking in security and surveillance applications is labor-intensive and often prone to human error, with existing semi-automated systems lacking effective tools to efficiently identify and distinguish between moving objects of interest and clutter or noise.
Innovation Solution
An alert and tracking system implemented on a computing device with a processor, featuring a display with a viewing portion and a raster portion, an image receiver, and a processing unit that compares images to detect changes, update the display, and add rasters representing moving objects, providing past location, direction, and size information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human operators manually monitor security areas, then detection capability is maintained, but labor intensity and operational costs increase
Solution Approach 1:
The patent replaces manual human monitoring with an automated computer-based system that captures images, compares them to detect changes, and generates alerts. This substitution eliminates the need for continuous human observation while maintaining detection capability, thereby improving operational efficiency without sacrificing reliability.
2Productivity
If semi-automated systems highlight moving objects, then detection efficiency improves, but ability to distinguish relevant objects from clutter deteriorates
Solution Approach 1:
The system provides feedback to operators by generating alerts only when significant changes are detected between sequential images. This selective alerting mechanism filters out insignificant movements and clutter, allowing operators to focus on truly relevant objects while maintaining high detection efficiency.
Solution Approach 2:
The patent extracts and highlights only the specific portions of images that contain significant changes or moving objects of interest. By isolating these relevant elements from the entire scene, the system improves detection efficiency while preventing information loss about object discrimination.
3Area of stationary object
If operators monitor large areas, then coverage increases, but attention and detection accuracy decrease
Solution Approach 1:
The system segments the monitoring area into discrete image frames captured at different time points. By comparing these segmented frames sequentially, the system can maintain high detection accuracy across large areas without requiring operators to divide their attention, as the automated system handles the comprehensive monitoring.
Data Source
AI summary
An alert and tracking system implemented on a computing device with a processor is presented. The system comprises a display with a viewing portion and a raster portion comprising a plurality of rasters. The system also comprises an image receiver configured to receive a first image and a second image, wherein the first image is received before the second image is received. The system also comprises a processing unit. The processing unit is configured to receive the second image. The processing unit is also configured to compare the second image to the first image. The processing unit is also configured to detect a change between the second image and the first image, wherein the detected change is indicative a moving object. The processing unit is also configured to update the viewing portion to display the second image. The processing unit is also configured to update the raster portion, wherein updating the raster image comprises adding a new raster to the plurality of rasters, wherein the new raster comprises a row of pixels corresponding to a compressed view of the image.