# An FPGA-Based Reconfigurable Accelerator for Real-Time Affine Transformation in Industrial Imaging Heterogeneous SoC

## TL;DR

This paper introduces an FPGA-based accelerator for real-time image correction in industrial imaging, achieving high speed and efficiency.

## Contribution

A novel reconfigurable accelerator architecture using a heterogeneous SoC with a multiplication-free PATRM algorithm for affine transformation.

## Key findings

- The accelerator achieves 25 FPS for 2095×2448 resolution images with 128.21 M pixel/s throughput.
- It is 5.3× faster than the Block AT baseline with PSNR exceeding 26 dB.
- The design supports real-time industrial scanner correction with low resource consumption.

## Abstract

Real-time affine transformation, a core operation for image correction and registration of industrial cameras and scanners, faces challenges including the high computational cost of interpolation and inefficient data access. In this study, we propose a reconfigurable accelerator architecture based on a heterogeneous system-on-chip (SoC). The architecture decouples tasks into control and data paths: the ARM core in the processing system (PS) handles parameter matrix generation and scheduling, whereas the FPGA-based acceleration module in programmable logic (PL) implements the proposed PATRM algorithm. By integrating multiplication-free design and affine matrix properties, PATRM adopts Q15.16 fixed-point computation and AXI4 burst transmission for efficient block data prefetching and pipelined processing. Experimental results demonstrate 25 frames per second (FPS) for 2095×2448 resolution images, representing a 128.21 M pixel/s throughput, which is 5.3× faster than the Block AT baseline with a peak signal-to-noise ratio (PSNR) exceeding 26 dB. Featuring low resource consumption and dynamic reconfigurability, the accelerator meets the real-time requirements of industrial scanner correction and other high-performance image processing tasks.