一种浮选泡沫视频图像自适应筛选方法

Adaptive filter algorithm of froth flotation video image

针对浮选视频图像获取过程中出现的图像质量问题,提出一种浮现泡沫视频图像自适应筛选方法。首先通过分析浮选图像纹理特征选取评价参数,然后采用改进BP神经网络建立图像质量评判模型,对不同质量图像进行评判筛选。实验证明,该方法筛选速度快且识别正确率和效率高,筛选后的图像分割效果好。

This paper proposed an adaptive filtering algorithm for flotation froth image of video. The algorithm was used to filter froth images that have poor quality. By analyzing the flotation image texture features, it decided the evaluating parameters. Then, it established image quality evaluation model based on improved BP neural network to judge and filter different quality images. The experiments show that the algorithm can fast and correctly filter images with different quality, and the result of segment for filtered flotation images is perfect.