[1] In the past, texture-based classification of soils has been used for grouping soils in variably saturated water flow and solute transport studies. Classification of soils becomes especially important for large-scale studies where the spatial and temporal variability in the hydraulic properties of soils exceeds the field sampling capabilities. Although soiltexture-based classification has be...

Luminance, colour and/or texture features may be used, either alone or in combination, for segmentation. In this paper luminance and colour classes are described using the corresponding empirical probability distributions. For texture analysis and characterisation a multichannel scale/orientation decomposition is performed using Wavelet Frame Analysis. Knowing only the number of the di erent cl...

As a representative of the linear discriminant analysis, the Fisher method is most widely used in practice and it is very effective in twoclass classification. However, when it is expanded to a multi-class classification problem, the precision of its discrimination may become worse. A main reason is an occurrence of overlapped distributions on the discriminant space built by Fisher criterion. I...

In terms of food safety, it is important to use the lands correctly in agricultural production. this study, potential crop suitability classes for wheat cultivation were created by using fuzzy model and GIS together. Spatial spectral factors considered as inputs separated four main groups, such soil (drainage, depth, texture, CaCO3, stoniness, pH, organic matter, salinity, ESP), topography (slo...

In this paper, we present a theoretically and computationally simple but efficient approach for rotation invariant texture classification. This method is based on new texture signatures extracted from spectrum. Rotation invariant texture features are obtained based on the extension of the derived signatures. The features are tested with 1000 randomly rotated samples of 20 Brodatz texture classe...

This chapter reviews and discusses various aspects of texture analysis. The concentration is on the various methods of extracting textural features from images. The geometric, random field, fractal, and signal processing models of texture are presented. The major classes of texture processing problems such as segmentation, classification, and shape from texture are discussed. The possible appli...

This paper proposes a method for classification and discrimination of textures based on the energies of image subbands. We show that even with this relatively simple feature set, effective texture discrimination can be achieved. In this paper, subbandenergy feature sets extracted from the following typical image decompositions are compared: wavelet subband, uniform subband, discrete cosine tran...

Selo District has great potential for developing plantation crops; however, the amount of production still needs to grow. The purpose this study is determine soil suitability class crops (arabica coffee, tobacco, cloves, cocoa, and tea), identify limiting factors in area, suggest ways overcome them increase land classes. was conducted District, Boyolali Regency from November 2022 - December 202...

This paper presents a method for applYIng mducllve learnmg techniques [0 tel{ture description Jnd recogmtlon. Local features of texture are computed by tWO well-known methods. Laws' masks and cO-Q<;currence matnces. Then. a three-level generalizaliOll of local features IS applied (0 .:reate teltture descnpllon rules. The fU"St level genera/ization. the scaling intertace. has been implemented to...

Since thematic classes are represented with high spectral variance, pixel-based classifications generally result with incontinuous and inhomogeneous outputs. Objectbased classifications overcome this problem by the approach similar to human seeing and interpreting activity. First, image is segmented into smaller objects, and then image objects are assigned to classes according to their spectral...