基于视觉感知机制的织物疵点轮廓检测

针对传统人工织物疵点检测存在的误检及低效等问题,提出了一种基于视觉感知机制的自适应织物疵点轮廓检测方法.首先,模拟视觉系统中视网膜感受野对视觉信息的处理机制对织物疵点图像进行滤波及疵点增强;其次,依据初级视皮层(V1)区对视觉信息响应的方向选择性机制构建织物疵点图像边缘检测模型,实现对织物疵点图像的边缘检测.最后,采用自适应阈值选择的方法对检测到的边缘进行二次处理,获得织物图像疵点的轮廓.为验证本文方法的有效性和准确性,对4类织物疵点图像进行测试,并定性和定量两方面进行比较分析,结果表明文中提出的方法能够较好地检测出织物疵点轮廓信息,不仅可以得到质量较高的织物疵点轮廓图像,而且在整个检测过程中能够自适应的选择参数,避免受人的主观因素影响,具有实际的应用价值.

Fabric Defect Contour Detection Based on Visual Mechanism

With regard to erroneous detection and low efficiency problems in the traditional manual detection of fabric defects, a self-adaptive detection method for fabric defect contours is proposed based on the visual perceptual mechanism. Firstly, the mechanism of visual information processing with the receptive field of the retina in the visual system is simulated to filter the fabric defect images and enhance the defects. Secondly, the edge information in the enhanced fabric defect images is detected according to the edge detection model of fabric defects proposed on the basis of the orientation selectivity mechanism in the area of primary visual cortex (V1). Lastly, the fabric defect contour is extracted by re-processing the detected edge images through self-adaptive threshold selection. To validate the effectiveness and accuracy of our method, this paper tests and compares four kinds of fabric defects from both qualitative and quantitative aspects. The results show that the proposed method performs well in detecting the contour information of fabric defects. This method not only acquires relatively high-quality detection images of fabric defects but also selects parameters adaptively in the whole process. It avoids the effect of subjective factors and implies practical application value.