The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.03 - May/June (2011 vol.13)
pp: 46-52
Karin S. Komati , Federal University of Espirito Santo
Evandro O.T. Salles , Federal University of Espirito Santo
Mario Sarcinelli-Filho , Federal University of Espirito Santo
ABSTRACT
<p>This fully automated process uses edge map information to eliminate false boundaries in an image's region map, and region map information to remove noise in its edge map. It then integrates the two maps into a single, final result. Experiments on a large dataset of natural color images show that this approach matches human perception better than individual methods in terms of both quantity and quality.</p>
INDEX TERMS
Region growing, edge detection, image processing, image segmentation, color segmentation, scientific visualizations, scientific computing
CITATION
Karin S. Komati, Evandro O.T. Salles, Mario Sarcinelli-Filho, "KSS: Using Region and Edge Maps to Detect Image Boundaries", Computing in Science & Engineering, vol.13, no. 3, pp. 46-52, May/June 2011, doi:10.1109/MCSE.2010.148
REFERENCES
1. X. Muñoz et al., "Strategies for Image Segmentation Combining Region and Boundary Information," IEEE Pattern Recognition Letters, vol. 24, nos. 1–3, 2003, pp. 375–392.
2. D. Martin et al., "A Database of Human Segmented Natural Images and Its Application to Evaluating Segmentation Algorithms and Measuring Ecological Statistics," Proc. 8th IEEE Int'l Conf. Computer Vision, vol. 2, IEEE CS Press, 2001, pp. 416–423.
3. K.S. Komati, E.O.T. Salles, and M. Sarcinelli-Filho, "Unsupervised Color Image Segmentation Based on Local Fractal Dimension," Proc. 17th Int'l Conf. Systems, Signals and Image Processing (IWSSIP 2010), IEEE Press, vol. 1, 2010, pp. 243–246.
4. Z. Pan and J. Lu, "A Bayes-Based Region-Growing Algorithm for Medical Image Segmentation," Computing in Science & Eng., vol. 9, no. 4, 2007, pp. 32–38.
5. Y. Deng and B.S. Manjunath, "Unsupervised Segmentation of Color-Texture Regions in Images and Video," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, no. 8, 2001, pp. 800–810.
6. K.F. Côco, E.O.T. Salles, and M. Sarcinelli-Filho, "Topographic Independent Component Analysis Based on Fractal and Morphology Applied to Texture Segmentation," LNCS 5441, Springer Verlag, 2009, pp. 491–498.
7. A. Conci and E.O. Nunes, "Multi-Bands Image Analysis Using Local Fractal Dimension," Proc. 14th Brazilian Symp. Computer Graphics and Image Processing (SIBGRAPI'01), vol. 1, IEEE CS Press, 2001, pp. 91–98.
8. R. Vuduc, "Image Segmentation Using Fractal Dimension," IEEE Trans. Circuits and Systems for Video Technology, vol. 5, no. 6, 1997, pp. 567–570.
9. R. Gonzalez and R. Woods, Digital Image Processing, 2nd ed., Prentice Hall, 2002.
10. M. Kuwahara et al., "Processing of Riangiocardiographic Images," Digital Processing of Biomedical Images, Plenum, 1976, pp. 187–203.
11. O. Rotem, H. Greenspan, and J. Goldberger, "Combining Region and Edge Cues for Image Segmentation in a Probabilistic Gaussian Mixture Framework," Proc. 2007 IEEE Conf. Computer Vision and Pattern Recognition, IEEE CS Press, 2007, pp. 1–8.
28 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool