학술논문

An Adaptive Method for Efficient Detection of Salient Visual Object from Color Images
Document Type
Conference
Source
2010 20th International Conference on Pattern Recognition Pattern Recognition (ICPR), 2010 20th International Conference on. :2346-2349 Aug, 2010
Subject
Computing and Processing
Image segmentation
Image color analysis
Visualization
Pixel
Color
Computer vision
Partitioning algorithms
graph-based segmentation
color segmentation
visual syntactic features
Language
ISSN
1051-4651
Abstract
This paper presents an efficient graph-based method to detect salient objects from color images and to extract their color and geometric features. Despite of the majority of the segmentation methods our method is totally adaptive and it do not require any parameter to be chosen in order to produce a better segmentation. The proposed segmentation method uses a hexagonal structure defined on the set of the image pixels ant it performs two different steps: a pre-segmentation step that will produce a maximum spanning tree of the connected components of the visual graph constructed on the hexagonal structure of an image, and the final segmentation step that will produce a minimum spanning tree of the connected components, representing the visual objects, by using dynamic weights based on the geometric features of the regions. Experimental results are presented indicating a good performance of our method.