The present work aims to bring out a new approach of features selection for the discrimination of textures in sequences of images containing moving objects. The moving textures are analysed using spatio-temporal co-occurrence matrices from which we extract features characterizing the textures themselves as well as their movements. The originality of this approach is to select features that allo...

An expanded model for the thermodynamics of co-clusters and their strengthening is presented, and the model is applied to predict co-cluster formation and strengthening in AlMg-Si alloys. The models are tested against data on a wide range of Al-Mg-Si alloys aged at room temperature. The strengthening due to co-clusters is predicted well. The formation of the co-clusters is studied in an Al-0.5a...

This paper describes that actomyosin complex particles are automatically selected. We propose a new approach, which combines both gray level co-occurrence matrix to extract texture features and SVM classifier to detect actomyosin complex particles automatically. Experimental results show that detection rate achieves 93.58%, the false positive rate is 3.66%, and the area under the ROC curve (AUC...

In this paper we propose a technique for classifying images by modeling features extracted at di erent scales. Speci cally, we use texture measures derived from Pap smear cell nuclei images using a Grey Level Co-occurrence Matrix (GLCM). For a texture feature extracted from the GLCM at a number of distances we hypothesise that by modeling the feature as a continuous function of scale we can obt...

Noises are always present in an image posing higher or lower complexity in removal and however it is necessary to remove those noises to obtain a better image. There are various types of filters available that help us to remove those noises; only when a right type of filter is used the best result could be obtained. This paper compares the performance of filters namely median, Weiner, average a...

Statewide land cover change detection analysis provides a useful tool for conservation planning and environmental monitoring and addresses issues of habitat fragmentation and urban sprawl. Furthermore, using historical and recent land cover data offers two perspectives on landscape dynamics. To this end, the first alliance level land cover map of Kansas recently completed by the KARS Program wa...

Camera model identification is of interest for many applications. In-camera processes, specific of each model, leave traces that can be captured by features designed ad hoc, and used for reliable classification. In this work we investigate on the use of blind features based on the analysis of image residuals. In particular, features are extracted locally based on co-occurrence matrices of selec...

Seismic interpretation can be supported by seismic attribute analysis. Common seismic attributes use mathematical relationships based on the geometry and the physical properties of the subsurface to reveal features of interest. But they are mostly not capable of describing the spatial arrangement of depositional facies or reservoir properties. Textural attributes such as the grey level co-occur...

Background: Although phytoremediation is a promising method for pollution control, biomass produced by the remediation process must be managed; otherwise, it will eventually return to the environment and cause secondary pollution. Therefore, research and policy development for the post-remediation management of biomass are both required. Results: While there are many published studies of phytor...