Search results for " Matched Filter"
showing 3 items of 3 documents
Automatic Extraction of Blood Vessels, Bifurcations and End Points in the Retinal Vascular Tree
2008
In this paper we present an effective algorithm for automated extraction of the vascular tree in retinal images, including bifurcations, crossovers and end-points detection. Correct identification of these features in the ocular fundus helps the diagnosis of important systematic diseases, such as diabetes and hypertension. The pre-processing consists in artefacts removal based on anisotropic diffusion filter. Then a matched filter is applied to enhance blood vessels. The filter uses a full adaptive kernel because each vessel has a proper orientation and thickness. The kernel of the filter needs to be rotated for all possible directions. As a consequence, a suitable kernel has been designed …
Hybrid Procedure for Automated Detection of Cracking with 3D Pavement Data
2016
Pavement cracks are considered a major indicator of pavement performance. Because traditional manual crack surveys are dangerous, time consuming, and expensive, technologies have been developed to collect high-speed pavement images, and numerous algorithms have been proposed to detect cracks on pavement surface. The latest PaveVision3D Ultra system (3D Ultra) has been implemented to achieve 30-kHz three-dimensional (3D) scanning rate for 1-mm resolution pavement surface data at highway speed up to 100 km/h (60 mi/h). This paper presents the application of a hybrid procedure for automated crack detection on 3D pavement data collected using 3D Ultra. The procedure combines three different me…
Optic disc positioning and blood vessels extraction on eye fundus
2009
This paper presents two methods aimed to the optic disc positioning on the retinal images. The first is based on a template of the entire image, while the second is based on the retinal vascularisation. For this second task, also a vessel extraction method is provided. Both the algorithm have been tested on test images of the Drive Database.