Automated Object Detection via Image Comparison
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Security cameras require continuous human monitoring to detect theft or changes in merchandise, making it difficult to notice small items missing unless actively watched, as the feed does not easily reveal such discrepancies.
Innovation Solution
A system for shape/object recognition using still/scan/moving image optical digital media processing, which includes a user device, capturing device, and cloud/server, utilizing detection software to compare reference images with subsequent images for object detection and analysis, providing notifications of any changes or discrepancies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If security cameras are used to monitor merchandise, then security coverage is provided, but continuous human monitoring is required which is impractical and time-consuming
Solution Approach 1:
The system enables self-service security monitoring by automatically comparing images against reference data and generating alerts without human intervention. The processor autonomously detects discrepancies, identifies objects, and notifies users, eliminating the need for continuous human watching while maintaining reliable security detection.
Solution Approach 2:
The patent replaces the mechanical system of human visual monitoring with an automated optical-digital processing system. Image capture devices, processors, and software algorithms substitute for human eyes and brain, automatically analyzing visual data to detect theft or changes in merchandise.
2Measurement precision
If human operators continuously watch security feeds, then small missing items can be detected, but the complexity and cost of manual monitoring increases
Solution Approach 1:
The system creates digital copies of the monitored space through image capture and stores reference data representing the normal state. By comparing current images against these digital references, the system achieves precise detection of small missing items without requiring complex manual inspection procedures.
Solution Approach 2:
The patent introduces an intermediary automated processing system between the physical merchandise and the human operator. The processor and software act as intermediaries that automatically analyze images, detect discrepancies, and present findings to users, simplifying the overall monitoring system while maintaining high detection precision.
3Reliability
If security personnel manually inspect camera feeds, then theft can be detected, but productivity and response time are reduced
Solution Approach 1:
The system performs preliminary action by pre-capturing reference images of the normal state and automatically comparing current images against these references. This preliminary setup enables rapid, continuous monitoring without requiring real-time human analysis, significantly improving productivity while maintaining reliable theft detection.
Solution Approach 2:
The patent implements feedback by automatically generating alerts when discrepancies are detected between current and reference images. This immediate feedback mechanism notifies users of potential theft or changes in real-time, eliminating the delays associated with manual inspection and大幅提升 security monitoring efficiency.
Data Source
AI summary
There is provided a system and method for shape/object recognition using still/scan/moving image optical digital media processing. The system may include a user device and a cloud/server. The user device may be configured to capture a reference optical data using a capturing device, transmit the reference data to the cloud/server, capture a subsequent optical data using the capturing device, and transmit the subsequent optical data to the cloud/server. The cloud/server may be configured to receive the reference optical data from the user device, receive the subsequent optical data from the user device, compare the subsequent optical data to the reference optical data, and transmit a notification to the user device. The notification may include similarities and differences between the reference optical data and the subsequent optical data.