School of Information Electrical and Engineering, Hunan University of Science and Technology, Xiangtan, China.
School of Information Science and Engineering, Central South University, Changsha, China.
PLoS One. 2019 Jan 10;14(1):e0210411. doi: 10.1371/journal.pone.0210411. eCollection 2019.
With the increase of the camera resolution, the number of pixels contained in froth image is increased, which brings many challenges to image segmentation. Froth size and distribution are the important index in froth flotation. The segmentation of froth images is always a problem in building flotation model. In segmenting froth images, Otsu method is usually used to get a binary image for classification of froth images, this method can get a satisfactory segmentation result. However, each gray level is required to calculate each of the between-class variance, it takes a longer time in froth images with a large number of pixels. To solve this problem, an improved method is proposed in this paper. Most froth images have the pixel distribution characteristic that the gray histogram curve is a sawtooth shape. The proposed method uses polynomial to fit the curve of gray histogram and takes the characteristic of gray histogram's valley into consideration in Otsu method. Two performance comparison methods are introduced and used. Experimental comparison between Otsu method and the proposed method shows that the proposed method has a satisfactory image segmentation with a low computing time.
随着相机分辨率的提高，泡沫图像中包含的像素数量增加，这给图像分割带来了许多挑战。泡沫大小和分布是泡沫浮选的重要指标。泡沫图像的分割一直是建立浮选模型的一个问题。在分割泡沫图像时，通常使用 Otsu 方法将其转换为二值图像，以便对泡沫图像进行分类，这种方法可以得到满意的分割结果。然而，对于具有大量像素的泡沫图像，需要计算每个灰度级的类间方差，这需要更长的时间。为了解决这个问题，本文提出了一种改进的方法。大多数泡沫图像具有像素分布特征，即灰度直方图曲线呈锯齿形。所提出的方法使用多项式来拟合灰度直方图的曲线，并在 Otsu 方法中考虑了灰度直方图的谷值特征。引入并使用了两种性能比较方法。Otsu 方法和所提出的方法的实验比较表明，所提出的方法具有令人满意的图像分割效果，计算时间短。
