.png){kind=icon}
.png){kind=icon}
Return
Color edge detection using the minimal spanning tree
.png){kind=icon}
PRE
AI
DOI：10.1016/j.patcog.2004.09.009.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this study, the edge detection task in vector-valued images is examined as a clustering problem. Using samples within a data window, the minimal spanning tree (MST) provides the ordering of multivariate observations and facilitates the identification of similar classes. The edge detector parameters like edge strength, type and orientation are subsequently determined from the clustered data. Experiments and comparisons are performed. revealing the enhanced performance of the proposed approach. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
Keywords:
edge detection
minimal spanning tree
multimodal distribution
ordering multivariate data
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.6
Papers:
1.3W
Citations:
4.5W
Organization
No organization information available