基于图像处理的药片包装视觉检测系统滤波算法

目的为了有效滤除药片包装视觉检测系统中的噪声,提升图像清晰度,保证后期图像分割、边缘处理顺利进行。方法针对药片视觉检测图像中存在大量不确定噪声,提出一种自适应模糊神经网络的图像滤波算法。在模糊神经网络结构中引入一个鲁棒性较强的隶属函数,并通过梯度下降法对模糊神经网络中的参数进行优化训练,利用优化后的网络结构对被噪声污染的图像进行滤波处理。结果仿真结果表明,该算法能够在保留较完整的图像边缘和重要细节的前提下,有效滤除药片中的噪声。结论该滤波算法有效提高了药片图像的清晰度,对于后期药片图像分割以及边缘化处理具有重要意义。

Filtering Algorithm of Tablet Packaging Visual Inspection System Based on Image Processing

The work aims to effectively remove the noise in the visual inspection system of tablet packaging, to enhance the image clarity and ensure that the later image segmentation and edge processing is carried out smoothly. For a large number of uncertain noises in the visual inspection images of tablets, an image filtering algorithm of the adaptive fuzzy neural network was proposed. A robust membership function was introduced in the fuzzy neural network structure, and the optimization training on the parameters of fuzzy neural network was carried out in the gradient descent method. The images with noise were filtered by the optimized network structure. The simulation results showed that the proposed algorithm could eliminate the noise of the tablet whiling preserving complete image edge and important details. The proposed filtering algorithm can effectively improve the tablet image clarity, and is of great significance for the later tablet image segmentation and edge processing.