Abstract: The remote sensing images are increasing day by day therefore storage and retrieval of these images is of significant importance. In this paper a prototype model for retrieval of remote sensing images on the basis of color moment and gray level co-occurrence matrix feature is developed and different vegetation index feature is extractor as color, texture and spectral. These three feat...

Clustering of the texture images is a demanding part of multimedia database mining. Most of the natural textures are non-homogenous in terms of color and textural properties. In many cases, there is a need for a system that is able to divide the non-homogenous texture images into visually similar clusters. In this paper, we introduce a new method for this purpose. In our clustering technique, t...

The use of the second order statistical measures has became popular in the image database indexing and retrieval. Unlike the common approach, image histogram, second order statistics like image correlogram and autocorrelogram consider also the spatial organization of the image colors or gray levels. Recently, correlograms and autocorrelograms have been widely used in the image database indexing...

Recently, the research towards Brodatz database for texture classification done at considerable amount of study has been published, the effective classification are vulnerable towards for training and test sets. This study presents the novel texture classification method based on feature descriptor, called spatial cooccurrence with discrete shearlet transformation through the LPboosting classif...

Maps of forest biomass are important tools for managing natural resources and reporting terrestrial carbon stocks. Using the San Juan National Forest in Southwest Colorado as a case study, we evaluate regional biomass maps created using physical variables, spectral vegetation indices, and image textural analysis on Landsat TM imagery. We investigate eight gray level co-occurrence matrix based t...

Markov/Gibbs random elds have been used for posing a variety of computer vision and image processing problems. Many of these problems are then solved using a simulated annealing type of method which involves the varying of the \temperature," a scale parameter for the model. In this paper we analyze the eeect of temperature on random eld texture patterns. We obtain new results relating structure...

The existing word representation methods mostly limit their information source to word co-occurrence statistics. In this paper, we introduce ngrams into four representation methods: SGNS, GloVe, PPMI matrix, and its SVD factorization. Comprehensive experiments are conducted on word analogy and similarity tasks. The results show that improved word representations are learned from ngram cooccurre...

A novel approach utilized in video database objectbased queries is proposed. This new method segments an example video sequence into real world objects using a combination of color image segmentation techniques along with MPEG-1/2 motion vectors. First, the initial frame in the sequence undergoes a color/texture segmentation algorithm that divides the frame into homogenous regions of color and ...

We present a fast, efficient, and automatic method for extracting vessels from retinal images. The proposed method is based on the second local entropy and on the gray-level co-occurrence matrix (GLCM). The algorithm is designed to have flexibility in the definition of the blood vessel contours. Using information from the GLCM, a statistic feature is calculated to act as a threshold value. The ...

We have investigated a combination of statistical modelling and expectation maximisation for a texture based approach to the segmentation of mammographic images. Texture modelling is based on the implicit incorporation of spatial information through the introduction of a set-permutation-occurrence matrix. Statistical modelling is used for data generalisation and noise removal purposes. Expectat...