Multi-Camera Surveillance Image Processing with FPGA Parallel Scaling
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Solution Overview
Problem
Existing surveillance systems struggle to efficiently process high-resolution image data from multiple camera modules, leading to resource inefficiencies and potential errors.
Innovation Solution
A surveillance system is designed with a network camera comprising multiple camera modules sharing an IP address, utilizing a communication module to receive and process image data, a decoder to decode, a scaler to scale, a multiplexer to combine, and an encoder to encode the data, ensuring the sum of scaled resolutions meets client terminal requirements, and an FPGA device for separate processing to prevent time differences and increase speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple camera modules process high-resolution image data through one processor, then surveillance coverage is improved, but processing efficiency deteriorates
Solution Approach 1:
The patent divides the processing system into multiple independent processing units (FPGA devices), each handling specific camera modules. This segmentation allows parallel processing of image data from multiple cameras simultaneously, maintaining high processing efficiency while expanding surveillance coverage.
Solution Approach 2:
The patent transitions from a single-processor sequential processing model to a multi-FPGA parallel processing architecture. By adding the dimension of parallel processing across multiple devices, the system can handle high-resolution data from multiple cameras without sacrificing processing speed.
2Device complexity
If one processor handles all image data from multiple cameras, then system complexity is reduced, but processing speed deteriorates
Solution Approach 1:
The system is segmented into multiple FPGA processing units, each responsible for specific camera modules. This division enables concurrent processing operations across separate hardware units, dramatically increasing processing speed while maintaining manageable complexity through modular design.
Solution Approach 2:
Multiple FPGA devices are merged into a coordinated processing system where each unit handles specific tasks. The combination of parallel processing capabilities from multiple devices achieves high-speed processing without requiring a single overly complex processor.
3Measurement precision
If high-resolution image data is processed in real-time, then image quality is improved, but resource consumption increases
Solution Approach 1:
The processing workload is segmented across multiple FPGA devices, distributing resource consumption rather than concentrating it in a single processor. This allows real-time processing of high-resolution data while managing energy and computational resources efficiently across the distributed system.
Solution Approach 2:
Each FPGA processing unit independently handles its assigned camera modules' data processing, making autonomous decisions about resource allocation and processing priorities. This self-service capability optimizes resource usage for maintaining high image quality without excessive overall system consumption.
4Ease of operation
If multiple camera modules share one IP address, then network configuration is simplified, but data transmission efficiency deteriorates
Solution Approach 1:
The system introduces an intermediary layer (the host device or control unit) that manages communication between the network and multiple camera modules sharing an IP address. This intermediary handles data routing and transmission optimization, maintaining simplified network configuration while improving actual data transmission efficiency through intelligent traffic management.
Data Source
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AI summary
Provided is a surveillance system including a communication module configured to receive a plurality of pieces of image data obtained by a plurality of camera modules, receive a multiple image data request from a client terminal, and transmit a multiple image data response including multiple image data to the client terminal; and a processer configured to generate the multiple image data by scaling the plurality of pieces of image data in response to the multiple image data request and combining a plurality of pieces of scaled image data, wherein the plurality of camera modules share one internet protocol (IP) address.