基于DSP和图像分割的织物疵点实时检测方法

Real-time Fabric Defect Detection Based on DSP and Image Segmentation

摘要:

疵点自动检测是纺织品缺陷在线检测领域的一个研究热点；为满足高速实时疵点检测应用要求,构建了基于TMS320DM642的织物疵点检测硬件系统；该系统由光源与成像、图像采集与实时处理、结果显示与统计分析等部分组成,能充分利用数字信号处理器的高速运算能力,有效提高系统的检测速度；并提出一种基于自适应阈值分割的疵点检测算法,通过增强织物图像灰度直方图波谷对应阈值的检测概率,有效提高了疵点图像的分割准确性；最后,在所建硬件系统平台上利用该算法进行了棉坯布疵点检测实验,疵点检出率达到93.6%；结果表明,本系统可自动实时检测织物疵点,且检出效率高。

Abstract:

The automatic defect detection has been a research focus in the field of fabric defect detection on-line. To meet the application requirements for high-speed and real-time defect detection, a fabric defect detection hardware system based on TMS320DM642 is designed. The system is consisted of the following parts:illumination & imaging, image acquisition & real-time processing, result display & statistical analysis. It can take full advantage of the digital signal processors’ high-speed operation ability and improves the speed of detection effectively. This paper proposes an algorithm based on adaptive threshold segmentation for defect detection. This algorithm enhances the detection probability of the threshold value corresponded to the fabric images’ gray histogram troughs and improves the accuracy of detect images’ segmentation. The defect detection rate reaches 93.6% through cambrayon detection experiment using the algorithm based on the hardware system platform. The result shows that the system can achieve the automatic and real-time fabric defect detection and has the high detection efficiency.