Abstract

In practice, off-line fabric defect detection is a real-time inspection process, requiring both inspection system and detection algorithms capable of high real-time performance. This paper presents a computer vision-based platform for the fabric’s visual quality assurance. The proposed platform is composed of four subsystems including: fabric drive, illumination and imaging, image acquisition and processing and human–computer interaction. The design of high-performance embedded system based on FPGA + DSP architecture is presented and discussed. After that, an extensive discussion on system settings, real-time implementation issues are presented. Finally, a real-time inspection experiment on 160-m real-world fabrics with 11 defect types is conducted. The experiment results show the proposed platform exhibits a good real-time response, and can achieve an overall 89% detection rate with a low false alarm at a speed of 30 m/min.

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