In 1979 Haralick famously introduced a method for analyzing the texture of an image: a set of statistics extracted from the co-occurrence matrix. In this paper we investigate novel sets of texture descriptors extracted from the co-occurrence matrix; in addition, we compare and combine different strategies for extending these descriptors. The following approaches are compared: the standard appro...

We present a novel dedicated hardware system for the extraction of second-order statistical features from high-resolution images. The selected features are based on gray level co-occurrence matrix analysis and are angular second moment, correlation, inverse difference moment and entropy. The proposed system was evaluated using input images with resolutions that range from 512×512 to 2048×2048 p...

Stiffness matrix of the four-node quadrilateral plane stress element is decomposed into normal and shear components. A computer program is developed to obtain the straining modes using adequate and reduced integration. Then a solution for the problem of mixing straining modes is found. Accuracy of the computer program is validated by a closed-form stiffness matrix, derived for the plane rectang...

Texture is an important spatial feature, useful for identifying objects or regions of interest in an image. Statistical and structural approaches have extensively studied in the texture analysis and classif ication whereas little work has reported to integrate them. One of the most popular statistical methods used to measure the textural information of images is the grey-level co-occurrence mat...

In this paper, research carried out to test the wavelet and co-occurrence matrix based features for rotation invariant texture image retrieval using fuzzy logic classifier. Energy and Standard Deviation features of DWT coefficients up to fifth level of decomposition and eight features are extracted from co-occurrence matrix of whole image and each sub-band of first level DWT decomposition. The ...

Article history: Available online 25 December 2012 In this paper, the modified color motif co-occurrence matrix (MCMCM) is presented for content-based image retrieval. The proposed method collects the inter-correlation between the red, green, and blue color planes which is absent in color motif co-occurrence matrix. The proposed method integrates the MCMCM and difference between the pixels of a...

The textural and spatial information extracted from very high resolution (VHR) remote sensing imagery provides complementary information for applications in which the spectral information is not sufficient for identification of spectrally similar landscape features. In this study grey-level co-occurrence matrix (GLCM) textures and a local statistical analysis Getis statistic (Gi), computed from...

not heavy for windows which are not too large, such as those that should be used for segmentation purposes. Moreover, two points should be noted. First, for the parameters of the form ^g(\i—j\ )ps(i, j), the co-occurrence matrix need not be stored; in fact, in eqn. 1 the elements Ms(i, j) do not appear. Secondly, the number of grey levels K does not influence the computational complexity of the...

Rainfall-induced landslides are a major threat in the hilly and gully regions of the Loess Plateau. Landslide mapping via field investigations is challenging and impractical in this complex region because of its numerous gullies. In this paper, an algorithm based on an object-oriented method (OOA) has been developed to recognize loess landslides by combining spectral, textural, and morphometric...

This paper presents a portable vision system for forest surveying that can estimate the diameter of a target tree with a single " point and click ". Of specific interest is the texture segmentation algorithm used for accurately determining the boundaries of the target tree in a forest. This segmentation is challenging because the target may be occluding other, almost identical looking trees, cr...