针对掺气水流图象中气泡的提取问题,提出了一种基于块聚类的二维直方图综合算法.该算法首先采用将图象依次划分为不同大小的子块,并进行二值化处理的方法来解决强气泡信息遮蔽弱气泡信息的问题;然后用块聚类的方法识别出单纯背景子块,并对其进行特殊处理;接着对得到的二值图象进行评价子块划分,并依据所定义的评价函数进行气泡信息的综合处理;最后对原始图象中出现的,无法用图象分割手段分离的叠加气泡区域的面积,用统计特性分析的方法对其进行叠加纠正补偿,同时对所得到的气泡面积分布进行定量估计.大量的实验结果证明该算法是有效的.

A new method based on two dimensional histogram and block clustering is proposed in this paper, in order to extract bubbles in the aerated water flows images. Firstly, the original image was divided into sub-images with different sizes in this method, to solve the uneven illumination of the image, which was result from the high intensity of bubbles defilade the low intensity bubbles in the image, and then the binary image of the sub-images were obtained. Secondly, block clustering is used to recognize the pure background blocks and dispose them in a special way. Thirdly, the bubble information is analyzed based on the definition of an evaluation function and an evaluation block in the binary image. Finally, a statistical characteristic analysis method is used to compensatethe overlapping bubbles, which were appeared in the original image, and it is also impossible to get high-accurate bubbles size by the method of image segmentation, and at the same time, optimal quantificational estimation of the bubble area square distribution was obtained. Many experimental results show that the method is efficient.