关键词: 图像处理, 瑕疵检测, Gabor小波, 神经网络

Abstract: To achieve the fabric defects in online visual detection, an effective method is proposed by combining the Gabor wavelet function and neural network to extract optimal Gabor filter parameters. Through building a Gabor wavelet neural network model, with the Levenberg-Marquardt algorithm to find the optimal solution, this method reconstructs the non-defect fabric image offline, to weaken the impact of the texture of the fabric defect detection during online testing, so that the defects will be highlighted during the online real-time testing, and then the defect area can be segmented from the fused image. The experimental results of four typical defect images including stain, broken warp, oil stain, and hole prove that this method is effective.

Key words: image processing, defect detection, Gabor wavelet, neural network