Detection Region Setting Apparatus for Automated Surveillance
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Solution Overview
Problem
Current methods for setting detection regions in surveillance systems, such as those used for object removal detection, are complex and prone to inaccuracies, leading to increased operator workload and detection accuracy issues.
Innovation Solution
A setting apparatus and method that simplifies the detection region setup by inputting images with and without the object of detection, using a determination unit to define the detection region, reducing the number of steps and improving accuracy through image processing and vertex reduction techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If an operator manually sets a detection region using a pointing device, then the detection region can be defined, but the operation becomes complicated and the operator workload increases
Solution Approach 1:
The system automatically determines the detection region by comparing images with and without the object, eliminating the need for manual operator intervention. The apparatus performs self-service by autonomously identifying the object's position and defining the detection region boundaries through image processing algorithms.
Solution Approach 2:
The manual mechanical operation of using a pointing device to draw detection regions is replaced by an automated image processing system. The determination unit uses computational methods to automatically define the detection region based on image comparison, substituting the mechanical interaction with an automated digital process.
2Measurement precision
If an operator manually sets a detection region, then the region can be defined, but incorrect setting may result in lower accuracy of detection
Solution Approach 1:
The system uses feedback from image comparison to automatically adjust and determine the detection region. By comparing the first image (with object) and second image (without object), the determination unit receives feedback about the object's position and automatically defines the detection region boundaries to ensure accurate detection.
Solution Approach 2:
The system performs self-correction by automatically identifying the object's position through image comparison and adjusting the detection region accordingly. This eliminates human error in manual region setting and ensures the detection region is precisely defined based on the actual object position.
3Productivity
If multiple steps are involved in setting the detection region, then the region can be defined, but the number of steps increases operator workload
Solution Approach 1:
The patent combines multiple manual operations (selecting objects, defining boundaries, adjusting parameters) into a single automated process. The determination unit merges these separate steps by automatically performing all necessary operations to define the detection region based on image comparison, eliminating the need for sequential manual interventions.
Solution Approach 2:
The system performs preliminary actions by automatically analyzing the images and determining the detection region before the detection process begins. This preliminary automated determination eliminates the need for subsequent manual adjustments and reduces the overall time required for region setting.
Data Source
AI summary
A setting apparatus which sets a detection region for a detection process of detecting a change of an image within a detection region corresponding to an object of detection inputs a first image in which the object of detection is present and a second image in which the object of detection is not present and determines the detection region from the first image and the second image such that the detection process may be performed on a detection region of a third image.