A Recurrent Adaptive Network: Balanced Learning for Road Crack Segmentation with High-Resolution Images

Multi Resolution Fuzzy Segmentation of Satellite Images

Object-Oriented Method for Automatic Extraction of Road from High Resolution Satellite Images

As the information carried in a high spatial resolution image is not represented by single pixels but by meaningful image objects, which include the association of multiple pixels and their mutual relations, the object based method has become one of the most commonly used strategies for the processing of high resolution imagery. This processing comprises two fundamental and critical steps towar...

Neural Network-Based Learning Kernel for Automatic Segmentation of Multiple Sclerosis Lesions on Magnetic Resonance Images

Background: Multiple Sclerosis (MS) is a degenerative disease of central nervous system. MS patients have some dead tissues in their brains called MS lesions. MRI is an imaging technique sensitive to soft tissues such as brain that shows MS lesions as hyper-intense or hypo-intense signals. Since manual segmentation of these lesions is a laborious and time consuming task, automatic segmentation ...

A-priori Information Driven Model for Road Segmentation in High Resolution Images

The problem of road segmentation in high resolution images is addressed in this paper. We present an extension of the active contour model that includes a-priori knowledge about the width of the roads being extracted. In order to improve the segmentation performance of the algorithm, the proposed model also contains a modified external energy term. The problem of the contour energy minimization...

Road Extraction from High Resolution Satellite Images

Roads are significant objects of an infrastructure and the extraction of roads from aerial and satellite images are important for different applications such as automated map generation and change detection. Roads are also important to detect other structures such as buildings and urban areas. In this paper, the road extraction approach is based on Active Contour Models for 1-meter resolution g...