Fast two-step segmentation of natural color scenes using hierarchical region-growing and a Color-Gradient Network

We present evaluation results with focus on combined image and efficiency performance of the Gradient Network Method to segment color images, especially images showing outdoor scenes. A brief review of the techniques, Gradient Network Method and Color Structure Code, is also presented. Different region-growing segmentation results are compared against ground truth images using segmentation evaluation indices Rand and Bipartite Graph Matching. These results are also confronted with other well established segmentation methods (EDISON and JSEG). Our preliminary results show reasonable performance in comparison to several state-of-art segmentation techniques, while also showing very promising results comparatively in the terms of efficiency, indicating the applicability of our solution to real time problems.

[1]  Michael M. Richter,et al.  Color image segmentation guided by a color gradient network , 2007, Pattern Recognit. Lett..

[2]  D. Mumford,et al.  Optimal approximations by piecewise smooth functions and associated variational problems , 1989 .

[3]  William M. Rand,et al.  Objective Criteria for the Evaluation of Clustering Methods , 1971 .

[4]  Zhenyang Wu,et al.  Natural color image enhancement and evaluation algorithm based on human visual system , 2006, Comput. Vis. Image Underst..

[5]  Luc Vincent,et al.  Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Ricardo M. L. Barros,et al.  Background recovering in outdoor image sequences: An example of soccer players segmentation , 2006, Image Vis. Comput..

[7]  G. Hartmann Recognition of Hierarchically encoded images by technical and biological systems , 2004, Biological Cybernetics.

[8]  Jing-Yu Yang,et al.  A fast watershed algorithm based on chain code and its application in image segmentation , 2005, Pattern Recognit. Lett..

[9]  Jong Won Park,et al.  Connectivity-based local adaptive thresholding for carotid artery segmentation using MRA images , 2005, Image Vis. Comput..

[10]  Jitendra Malik,et al.  A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[11]  Christopher V. Alvino,et al.  Fast Mumford-Shah segmentation using image scale space bases , 2007, Electronic Imaging.

[12]  Lutz Priese,et al.  Fast and Robust Segmentation of Natural Color Scenes , 1998, ACCV.

[13]  J. Douglas Birdwell,et al.  Efficient Implementation of the Chan-Vese Models Without Solving PDEs , 2006, 2006 IEEE Workshop on Multimedia Signal Processing.

[14]  Horst Bunke,et al.  Distance Measures for Image Segmentation Evaluation , 2006, EURASIP J. Adv. Signal Process..

[15]  Dorin Comaniciu,et al.  Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Minas E. Spetsakis,et al.  Tracking based motion segmentation under relaxed statistical assumptions , 2006, Comput. Vis. Image Underst..

[17]  Alain Trémeau,et al.  Regions adjacency graph applied to color image segmentation , 2000, IEEE Trans. Image Process..

[18]  B. S. Manjunath,et al.  Unsupervised Segmentation of Color-Texture Regions in Images and Video , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  T. Dudok de Wit,et al.  Fast Segmentation of Solar Extreme Ultraviolet Images , 2006 .