Automated extraction of roads from remotely sensed data come forth various usages ranging
from digital twins for smart cities, intelligent transportation, urban planning, autonomous …

Curvilinear object segmentation is a paramount step for many applications ranging from
medical to aerial image processing. In particular, vessel segmentation in retinal images …

Segmentation of curvilinear structures is important in many applications, such as retinal
blood vessel segmentation for early detection of vessel diseases and pavement crack …

Extracting roads from remote sensing images is of significant importance for automatic road
network updating, urban planning, and construction. However, various factors in complex …

Line detection is an essential procedure for many tasks in computer vision. Although
literature is rich in proposals for this topic, most of existing methods are vulnerable to noise …

This work applies sparse representations and nonlinear image processing to two inverse
imaging problems. The first problem involves image restoration, where the aim is to …

Many vision-based methods for defect detection have been proposed to replace inefficient
manual inspection. However, due to the complex shape and high degree of freedom …

Curvilinear object detection is the common denominator of several applications. Some
illustrative examples are road detection from aerial or satellite images, human airways from …

Automated extraction of roads from remotely sensed data come forth various usages ranging
from digital twins for smart cities, intelligent transportation, urban planning, autonomous …

Road extraction from remote sensing images is essential for autonomous driving, traffic
management, and map updating. Nevertheless, the result of road extraction might become …