An Application Approach to Kalman Filter and CT Scanners for Soil Science

摘要

Over the years, experts on soil science have brought together researchers from various fields with the aim of pooling efforts in order to characterize the properties of soils.The use of these results in agriculture through various activities can be directed towards a development whose natural resource base can be maintained in a long term.Conservation, minimization of soil pollution together with the development of irrigation and more efficient and more cost effective drainage systems optimize the efficiency of water use and nutrients in agricultural production.The soil can be preserved through management methods, which seek to prevent deterioration, induced erosion and deposition of sediments into rivers.Environment degradation can be caused naturally and by humans.The way in how to use the soil can cause degragation and excessive compression, salinisation and acidification.Several conventional techniques have been used to find answers to the various physical mechanisms and also the chemical and biological processes that occur in soils.Among those techniques are included: neutron probe, gravimetry, direct transmission of rays, plotters, microscopy and mercury intrusion, however these mechanisms have limitations.New techniques that enable an accurate prediction aim at managing the flow of contaminants through unsaturated soil zone.With the goals of acquiring non-invasive samples and reaching higher resolutions on and x-rays computerized tomography (CT) and on Nuclear Magnetic Ressonance (NMR), which provide cross-section images from the analysed objects.NMR, however, presents strong restrictions for its use in porous media that contain paramagnetic materials (Crestana & Nielsen, 1990) and, besides this, it is difficult or even impossible to quantify the results by correlating the NMR signal and the content of water.However, by means of CT it is possible to figure out a good correlation between the x-ray linear attenuation coefficients and the water content in soils.The quality of an image is one of the key requirements for its analysis and it is desirable that the reconstructed object is very close to the tested sample.The use of algorithms developed for the areas of human knowledge has grown considerably and has improved image processing for visual information analysis and human interpretation or the automatic perception of machines.In human interpretation, x-ray images are used not only in medicine, but also in geology, in archaeology, and in soil science for agricultural purposes. www.intechopen.comPrinciples, Application and Assessment in Soil Science 372On the other hand, the perception of automatic machines for present automatic recognition of faces, characters, fingerprints, computer vision, control of robots for surveillance, automatic processing of satellite images for fire recognition, climate change and identification of storms and hurricanes.Image processing aims at modeling the characteristic of the human eye, study processed images, such as Fourier transform and other separable image transforms.It also allows designing filters used to retrieve an image and use masks so that the processed image is more applicable than the original (real).This study aims at improving the quality of tomographic images by filtering the signals before their reconstruction and reaching an image quality in the reconstructed slice obtained by the projections close to the real one.Digital processing algorithms can be used to work with the image by using computer vision techniques such as segmentation (for feature extraction) and Hough transform (used in order to detect geometry, ie, detection of pores), which allow the count of pores in the soil.Classification algorithms can also be used to characterize the type of soil as well as its chemical components based on the values of pixels and density.Both kinds of algorithms can be an auxiliary tool for a reliable analysis on the impacts of the use of agricultural machinery on the soil, which