Road-following by mobile robots under varying outdoor illumination demands special care to be taken in road segmentation to h andle color ch anges in sunny or sh adow parts. T h is paper addresses th e tech nical feasibility of an automatic color evaluation meth od for fast segmentation of roads w ith unknow n geometrical sh apes. Instead of color segmentation in 2 D or 3 D color space, w e use...

The aim of this study is to develop automatic road extraction algorithm in satellite images. As roads have different width and surface material characteristics in urban and rural areas, a modular approach for road extraction algorithm is desired. In this study, edge detection, segmentation, clustering and vegetation and land cover analyses are used. In order to combine the results of different ...

In vision navigation tasks, the road segmentation is a useful method. Usually, roads can be detected using image segmentation and related image process methods. However such methods always rely on specific road prior knowledge, and they are difficult to be realized in different environments. In this paper the learning classification is proposed. In the learning process the roads of different en...

In this work a novel algorithm for lane marking and road-covering defects detection on rectified images of road covering is proposed. Proposed method is based on image over-segmentation and classification of resulting segments. We use cascaded classifiers for lane marking and road defects detection. Each cascade layer involves binary classification and the last layer involves multi-class classi...

A road segmentation technique is proposed based on a mathematical morphology tool called watershed transform. Starting from a coarse marker of the road to be segmented, we modify the gradient image of the scene and compute the watershed transform of this image. The result provides a fair segmentation of the road. The marker itself is produced by using the watershed transform, and a simplified r...

Image segmentation is an essential component of the remote sensing, image inspection, classification and pattern identification. The road satellite image categorization points a momentous tool for the assessment of images. In the present work, the researchers have evaluated the computer vision techniques for instance segmentation and knowledge based techniques for categorization of high-resolut...

Geo-specific road databases are sometimes necessary for driving simulation studies. However, manually creating them is very time consuming. One of the reasons is that a real road can have non-uniform cross sections due to irregular shaped road boundaries. Additionally, in the UCF driving simulator system, the road database format requires identification of repeatable cross sections, which is al...