DocumentCode :
3682973
Title :
IFT-SLIC: A General Framework for Superpixel Generation Based on Simple Linear Iterative Clustering and Image Foresting Transform
Author :
Eduardo Barreto Alexandre;Ananda Shankar Chowdhury; Falcão;Paulo A. Vechiatto Miranda
Author_Institution :
Dept. of Comput. Sci., Univ. of Sao Paulo, Sao Paulo, Brazil
fYear :
2015
Firstpage :
337
Lastpage :
344
Abstract :
Image representation based on super pixels has become indispensable for improving efficiency in Computer Vision systems. Object recognition, segmentation, depth estimation, and body model estimation are some important problems where super pixels can be applied. However, super pixels can influence the efficacy of the system in positive or negative manner, depending on how well they respect the object boundaries in the image. In this paper, we improve super pixel generation by extending a popular algorithm -- Simple Linear Iterative Clustering (SLIC) -- to consider minimum path costs between pixel and cluster centers rather than their direct distances. This creates a new Image Foresting Transform (IFT) operator that naturally defines super pixels as regions of strongly connected pixels by choice of the most suitable path-cost function for a given application. Non-smooth connectivity functions are also explored in our IFT-SLIC approach leading to improved performance. Experimental results indicate better super pixel extraction using the proposed approach as compared to that of SLIC.
Keywords :
"Image segmentation","Transforms","Clustering algorithms","Vegetation","Accuracy","Image color analysis","Shape"
Publisher :
ieee
Conference_Titel :
Graphics, Patterns and Images (SIBGRAPI), 2015 28th SIBGRAPI Conference on
Electronic_ISBN :
1530-1834
Type :
conf
DOI :
10.1109/SIBGRAPI.2015.20
Filename :
7314582
Link To Document :
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