Ulster University Logo

Ulster Institutional Repository

Edge Detecting for Range Data using Laplacian Operators

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Coleman, SA, Scotney, BW and Suganthan, S (2010) Edge Detecting for Range Data using Laplacian Operators. IEEE Transactions on Image Processing, 19 (11). pp. 2814-2824. [Journal article]

Full text not available from this repository.

DOI: 10.1109/TIP.2010.2050733

Abstract

Feature extraction in image data has been investigated for many years, and more recently the problem of processing images containing irregularly distributed data has become prominent. Range data are now commonly used in the areas of image processing and computer vision. However, due to the data irregularity found in range images that occurs with a variety of image sensors, direct image processing, in particular edge detection, is a nontrivial problem. Typically, irregular range data would require to be interpolated to a regular grid prior to processing. One example of an edge detection technique that can be directly applied to range images is the scan-line approximation, but this does not employ exact data locations. Therefore, we present novel Laplacian operators that can be applied directly to irregularly distributed data, and in particular we focus on application to irregularly distributed 3-D range data for the purpose of edge detection. Within the data distribution framework commonly occurring in range data acquisition devices, our results illustrate that the approach works well over a range of levels of irregularity of data distribution. The use of Laplacian operators on range data is also found to be much less susceptible to noise than the traditional use of Laplacian operators on intensity images.

Item Type:Journal article
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Information Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Information and Communication Engineering
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:16052
Deposited By:Dr Sonya Coleman
Deposited On:28 Oct 2010 16:09
Last Modified:15 Jun 2011 11:08

Repository Staff Only: item control page