Application of Improved K- means Algorithm in Microvadose Image Segmentation
نویسندگان
چکیده
Water flooding microscopic seepage experiment is an effective method to study the microvadose mechanisms as well as the distributions of remaining oil. Throughout the experiment the quantitative description of the porous medium fluid flow parameters such as porosity, oil saturation and so forth is crucial. A quantitative analysis method is proposed via image processing, including image preprocessing, image feature extraction, improvement of Kmeans algorithm, segmentation of flooding water, binding water, remaining oil and pores along with the calculation of seepage parameter, etc. An example is provided to demonstrate the validity of this method. Furthermore, microscopic seepage images can be divided automatically, accurately and efficiently.
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