The association rules algorithms can be used for describing textures if an appropriate texture representation formalism is used. This representation has several good properties like invariance to global lightness and invariance to rotation. Association rules capture structural and statistical information and are very convenient to identify the structures that occur most frequently and have the ...

A method to assess the aging of a human subject by modeling the devolution of the textural features in brain images using a backpropagation neural network (BPNN) is described in this paper. Normally, the brain white matter (BWM) undergoes degenerative changes in its physical and functional stochastics during the aging process. Relevant structural morphology observed in the brain complex can be ...

Image inpainting technique uses textural or structural information to repair or fill damaged potions of a picture. When dealing with a small area missing textural image, not only should guarantee the effectiveness of the algorithm, but the processing speed also need to be taken into account. In this paper, we propose a simply and effective inpainting method which combining fast inpainting metho...

Although mangrove is one of important ecosystems in the world, it has been abused and exploited by human for various purposes. Monitoring mangrove is therefore required to maintain a balance between economy and conservation and provides up-to-date information for rehabilitation. Optical remote sensing data have delivered such information, however ever-changing atmospheric disturbance may signif...

Introduction: Previous studies [1,2] have suggested that genetic subtypes of breast cancer are associated with distinct imaging phenotypes on DCEMRI. However, previous attempts to distinguish molecular subtypes of breast cancer are based on qualitative, visual examination of the tumors. In our previous work, we developed a computer aided diagnosis (CAD) system that exploited textural changes wi...

Spectral clustering methods have been shown to be effective for image segmentation. Unfortunately, the presence of image noise as well as textural characteristics can have a significant negative effect on the segmentation performance. To accommodate for image noise and textural characteristics, this study introduces the concept of sub-graph affinity, where each node in the primary graph is mode...

A novel approach using volumetric texture and reduced-spectral features is presented for hyperspectral image classification. Using this approach, the volumetric textural features were extracted by volumetric gray-level co-occurrence matrices (VGLCM). The spectral features were extracted by minimum estimated abundance covariance (MEAC) and linear prediction (LP)-based band selection, and a semi-...