Intelligent system for estimating porosity in building stones based on image processing and machine vision techniques

One of the main factors in the quality grading of building stones is porosity amount. On the other hand, the strength coefficient of the facade of the building against rain and freezing is also highly dependent on this factor. Currently, estimation of porosity and quality grading of stone in most stone cutting factories is done visually and by workers familiar with the work. This process is time-consuming and expensive for most factories. Therefore, in this article, a method for estimating the amount of porosity in building stones based on image processing techniques is presented. In this method, after taking a photo of the desired stone, the texture analysis algorithm is implemented on the image and finally a binary image is obtained in which the porous parts are separated from the healthy parts. In the resulting image, with the help of the surface comparison equation, the porosity of the stone can be calculated in terms of percentage. In the results section, this method has been tested on several models of building stones and its accuracy has been calculated. Among the advantages of the method, we can mention the low computational complexity, high execution speed and compatibility with most rock models.