In this paper a new quantitative tissue characterization (QTC) program was developed for computing a standardized sets of parameters and quantitative color-mapping of these parameters for non-invasive accurate diagnosis of liver pathologies. In this program, histogram, co-occurrence matrix, runlength matrix, gradient texture feature coding, backscattering, attenuation and speckle parameters wer...

Texture analysis and classification are usual tasks in pattern recognition. Rock texture is a demanding classification task, because the texture is often non-homogenous. In this paper, we introduce a rock texture classification method, which is based on textural and spectral features of the rock. The spectral features are considered as some color parameters whereas the textural features are cal...

Diffusion magnetic resonance imaging is presently widely used technique that allows measurement of white matter fiber orientation in the human brain. The connectivity complex of fiber tracts strongly influences the function of communicating large neuronal networks in the brain. In order to analyze the changes in white matter with respect to age, the textural features are computed from the spati...

This paper proposes an image textural analytical method for estimating the crowd density and counting. At first, the target detection is conducted to obtain the foreground image. This crowd image is used to calculate the gray level co-occurrence matrix (GLCM). Then, according to the characteristic values of the gray level co-occurrence matrix, i.e., energy, entropy, contrast, homogeneity, we us...

Semivariogram functions are compared to cooccurrence matrices for classification of digital image texture, and accuracy is assessed using test sites. Images acquired over the following six different spectral bands are used: 1) SPOT HRV, near infrared; 2) Landsat thematic mapper (TM), visible red; 3) India Remote Sensing (IRS) LISS-II, visible green; 4) Magellan, Venus, S-band microwave; 5) shut...

A robust thresholding technique is proposed in this paper for segmentation of brain MR images. It is based on the fuzzy thresholding techniques. Its aim is to threshold the gray level histogram of brain MR images by splitting the image histogram into multiple crisp subsets. The histogram of the given image is thresholded according to the similarity between gray levels. The similarity is assesse...

In this paper, a new image indexing and retrieval algorithm using multiresolution directional binary code (DBC) co-occurrence matrix is proposed. DBC histogram captures only the patterns distribution in a texture while the spatial correlation between the pair of patterns is gathered by DBC Co-occurrence. Multi-resolution texture decomposition and co-occurrence calculation has been efficiently u...

Principal Components Analysis (PCA) is the multivariate statistical technique employed to extract eigenvectors and eigenvalues from the contextual query co-occurrence matrix.

An optimal thenar palmprint classification model is proposed in this paper. Firstly, the thenar palmprint image is enhanced using a high-frequency emphasis filter and histogram equalization. Then, from the enhanced image thirteen textural features of gray level co-occurrence matrix (GLCM) are extracted as classification feature vectors. Finally, the SVM classifier is used for classification and...