Linear feature extraction and description

Real-time landing place assessment in man-made environments

“…There is a long tradition of detecting landing sites from aerial images, which dates back to the inception of our field [36]. Initial work focused on the detection of runways for the automated aerial mapping of airports [25,34,36,46].…”

“…Initial work focused on the detection of runways for the automated aerial mapping of airports [25,34,36,46]. Since then many automated landing approaches have been developed that considered the detection of both prepared and unprepared landing sites from both active and passive sensors in a variety of terrains.…”

Feature-Level Fusion in Personal Identification

“…In this study, an edge detector based on the algorithm of [18] is used followed by a thinning process to generate one-pixel wide edge curves. To generate the Line Edge Map (LEM), the dynamic two strip algorithm (Dyn2S) [19] is utilized to detect dominant points on the edge curves.…”

Fast Screening in Large Face Databases Using Merit-Based Dominant Points

“…It is a general method that any edge detector can be used. In this study, an edge detector based on the algorithm of Nevatia [6] is used followed by a thinning process to generate one pixel wide edge curves. The dynamic two-strip algorithm (Dyn2S) [10] is utilized to detect dominant points, the points with high curvatures, on the facial edge curves.…”

“…[2][3][4][5][6] are only a few examples from a large collection of algorithms that have been presented to the computer vision community. The continuing development of edge detectors is producing increasingly complex edge detection algorithms.…”