Union-Retire for Connected Components Analysis on FPGA.

Area of Science:

• Computer Science
• Digital Hardware Design
• Image Processing Algorithms

Background:

• Traditional connected components analysis (CCA) algorithms often rely on directed tree structures, leading to higher memory demands.
• Existing CCA methods can incur end-of-row processing overhead, impacting efficiency.
• The need for memory-efficient and streamlined CCA algorithms is critical for hardware implementations.

Purpose of the Study:

• To introduce a novel hardware architecture for the Union-Retire Connected Components Analysis (UR-CCA) algorithm.
• To analyze and address memory bandwidth and pipelining challenges in hardware-based UR-CCA.
• To demonstrate the resource savings achievable with the proposed UR-CCA hardware architecture on an FPGA.

Main Methods:

• Development of a hardware architecture specifically designed for the UR-CCA algorithm.
• Analysis of memory bandwidth requirements and pipelining strategies for efficient hardware implementation.
• Implementation and evaluation of the architecture on a Field-Programmable Gate Array (FPGA).

Main Results:

• The proposed hardware architecture successfully implements the UR-CCA algorithm, focusing on connectivity rather than directed trees.
• Memory bandwidth and pipelining challenges inherent in hardware UR-CCA were identified and resolved.
• A significant reduction of up to 36% in memory resources was achieved compared to conventional approaches.

Conclusions:

• The UR-CCA algorithm provides a memory-efficient alternative for connected components analysis.
• The developed FPGA architecture effectively addresses hardware implementation challenges.
• The proposed solution enables the creation of smaller, more resource-efficient devices for CCA applications.