Motion Detection System Using Pixel and Region Analysis
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Solution Overview
Problem
Existing monitoring systems face challenges in automatically detecting moving objects within a monitoring region due to limitations in effectively distinguishing between foreground and background, leading to increased personnel costs and restricted monitoring ranges.
Innovation Solution
A motion detection system combining pixel-based and region-based detection methods, utilizing a pixel-based detector to identify foreground regions, a region-based detector to validate peripheral pixels, and a motion determiner to select and refine the final motion region, thereby reducing noise and dynamic background errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a pixel-based motion detection method is used, then detection coverage is improved, but detection accuracy deteriorates due to noise and dynamic background
Solution Approach 1:
The patent segments the detection process into two independent stages: pixel-based detection for coverage and region-based detection for accuracy. The pixel-based detector identifies candidate regions, while the region-based detector validates them by analyzing peripheral pixels and luminance characteristics, effectively separating the functions of coverage and precision.
Solution Approach 2:
The patent merges pixel-based detection and region-based detection into a unified motion detection system. The pixel-based detector and region-based detector work together, with the latter refining the results of the former, to achieve both broad coverage and high accuracy in motion detection.
2Productivity
If automatic motion detection is implemented, then monitoring efficiency is improved, but detection reliability deteriorates due to false detection of dynamic background
Solution Approach 1:
The region-based detector acts as an intermediary between the pixel-based detector and the final motion detection result. It validates the candidate regions by analyzing peripheral pixels and luminance characteristics, filtering out false detections from dynamic background while maintaining the efficiency of automatic detection.
Solution Approach 2:
The region-based detector provides feedback to the pixel-based detector by validating each candidate region's peripheral pixels. This feedback mechanism ensures that only regions with consistent luminance characteristics across peripheral pixels are confirmed as true foreground objects, improving reliability while maintaining automation.
3Measurement precision
If region-based detection is added to pixel-based detection, then detection accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the detection system into two distinct modules: a pixel-based detector for initial candidate identification and a region-based detector for validation. This segmentation allows each module to specialize in specific tasks, improving accuracy while keeping the overall system architecture manageable through modular design.
Data Source
AI summary
Provided are a motion detection system and method. The motion detection system includes a pixel-based detector configured to compare a previous frame and a present frame to extract pixel constituting a first foreground region, a region-based detector configured to extract a second foreground region based on peripheral pixels of a pixel to be inspected, and a motion determiner configured to detect, as a final motion region among pixel groups of the first foreground region, a pixel group comprising pixels corresponding to the second foreground region.