Partial Image Matching for Low-Bandwidth Surveillance Transmission
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Solution Overview
Problem
Surveillance systems face challenges with blind spots due to fixed cameras and image compression artifacts, leading to unclear image data transmission and support services.
Innovation Solution
An image processing system with a terminal and server configuration that includes image accumulation, transmission, and matching units to manage and enhance image data transmission quality while reducing data size, using dynamic compression and object detection for efficient image processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If high-compression encoding schemes are applied to captured image data, then the amount of image data transmitted is reduced, but the image quality deteriorates with compressive artifacts
Solution Approach 1:
The image data is divided into multiple blocks or segments, and only certain blocks containing important information (such as regions with objects of interest) are transmitted in high quality, while other blocks are transmitted in lower quality or compressed form. This segmentation allows the system to reduce overall data transmission while preserving critical image quality.
Solution Approach 2:
Different quality levels are applied to different regions of the image based on their importance. Regions containing objects of interest or critical information are maintained in high quality, while less important background regions are heavily compressed. This local quality differentiation resolves the contradiction by preserving necessary image quality while reducing overall data volume.
2Ease of manufacture
If fixed surveillance cameras are used for crime prevention, then installation is simple and coverage is stable, but blind spots occur and visibility is limited
Solution Approach 1:
The system combines fixed surveillance cameras with mobile surveillance devices (such as wearable cameras or mobile robots). The fixed cameras provide stable baseline coverage, while mobile devices supplement blind spots and provide flexible repositioning. This merging of fixed and mobile systems resolves the contradiction by maintaining installation simplicity while dramatically improving coverage flexibility and eliminating blind spots.
3Measurement precision
If image data is transmitted with high quality to support service functions, then image matching accuracy improves, but data transmission load increases
Solution Approach 1:
Instead of transmitting entire high-quality images, the system extracts and transmits only the essential features or key regions required for service support functions such as image matching. This extraction approach maintains sufficient accuracy for the intended applications while dramatically reducing the data transmission load.
Solution Approach 2:
Image preprocessing and feature extraction are performed before transmission to identify and retain only the most important information. By performing preliminary actions to extract essential features, the system ensures that subsequent image matching operations can achieve high accuracy with significantly reduced data quantities.
Data Source
AI summary
The disclosed embodiments include computer-implemented devices, systems, and methods that support image processing services. In an embodiment, a server may match a partial image received from a terminal with stored candidate image in the memory, and upon identification of a match, transmit information identifying the matched candidate image to the terminal.