A RISC-V based image acquisition system using CIS for industrial print quality inspection

This paper presents an image acquisition system based on a Contact Image Sensor (CIS) for industrial print quality inspection and designs a specialized System-on-Chip (SoC) integrating control, image data acquisition, and transmission functionalities, leveraging the open-source Reduced Instruction Set Computer-V (RISC-V) architecture. The system combines the high integration and low-cost advantages of the CIS module with the flexibility and customizability of the RISC-V architecture, providing an efficient, low-cost, and real-time image acquisition solution. By precisely controlling a dual-axis motion platform, the system drives the CIS to perform real-time scanning of printed outputs, while transmitting the acquired data to a host computer for defect detection. A data mapping algorithm, together with a real-time data transfer mechanism and system framework based on multiple Direct Memory Access (DMA) buffering and interrupts, improves storage space utilization while ensuring data integrity, reliability, and real-time performance. Experimental results demonstrate that the system can efficiently and reliably acquire and transmit high-resolution images, meeting both image acquisition and real-time system requirements while significantly reducing hardware costs. In tests, the proposed solution improves storage utilization by approximately 25.7% and operational speed by 26.5% compared to traditional single-buffer serial transmission, with further gains as the size of the scanned images increases. This research not only provides an innovative, cost-effective solution for industrial print quality inspection but also enriches the RISC-V ecosystem and expands its application in industrial control domains. • Proposed a cost-effective system based on contact image sensors for print inspection. • A custom RISC-V SoC with Linux support was implemented and validated on FPGA. • Multi-DMA buffering improves real-time performance and storage utilization. • Developed a dual-port RAM-based algorithm to optimize image storage and processing.