DocumentCode
1788191
Title
Affiliation possibility map filtering for image segmentation improvement
Author
Mozdren, Karel ; Sojka, Eduard ; Surkala, Milan ; Fusek, Radovan
Author_Institution
FEECS, VrB-Tech. Univ. of Ostrava, Ostrava, Czech Republic
fYear
2014
fDate
14-17 Oct. 2014
Firstpage
1
Lastpage
6
Abstract
Image segmentation is an important task in computer vision. The task of image segmentation is to portion image into segments, thus provide more meaningful information of the image contents. Many methods have been developed for numerous application. The common problems of most of the segmentation techniques are scattered segmentation lines, too much details, small or thin segments, and noisy segmentation. In this paper, we propose a novel method for image segmentation improvement. We present state-of-the-art methods, our proposed method and experiments, showing performance over segmentations from classical image segmentation methods and also over segmentations from background subtraction methods.
Keywords
computer vision; image filtering; image segmentation; affiliation possibility map filtering; background subtraction method; computer vision; image segmentation; Computer vision; Educational institutions; Equations; Image edge detection; Image segmentation; Noise; Noise measurement; affiliation map; background subtraction; filter; image segmentation;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing Theory, Tools and Applications (IPTA), 2014 4th International Conference on
Conference_Location
Paris
Print_ISBN
978-1-4799-6462-8
Type
conf
DOI
10.1109/IPTA.2014.7001933
Filename
7001933
Link To Document