Studying Grout Propagation in Granular Soils by Image Processing Techniques

This article presents two image-processing techniques which allow studying grout propagation in granular soils. The first one deals with the evaluation of the cement grout concentration using UV spectrophotometry. The second is based on image segmentation processing: active contour model. We propose to develop the active contour model image analysis technique. This process, currently applied in the field of medicine, can be transposed to grout flow detection during soil injection. They are powerful image segmentation techniques that combine geometry, physics and approximation theory. Two distinct formulations exist to employ these techniques, parametric or geometric curves. These models have proven to be effective in segmenting and tracking non-rigid structures. They exploit features derived from the image data together with a prior knowledge about the location, size and shape of these structures. We focus on a parametric approach for deformable models. They support highly intuitive interaction mechanisms. Those mechanisms allow, when necessary, researchers to bring their expertise to bear on the model-based image interpretation task. In this paper, we show the development of the two different image analysis methods employed in our experiments for grout detection and grout concentration measurement.