Date of download: 6/22/2016 Copyright © 2016 SPIE. All rights reserved. Examples of different class maps. The homogeneity-related measure J is 1.29, 0, and 0.60 respectively. Figure Legend: From: Image segmentation by optimizing a homogeneity measure in a variational framework J. Electron. Imaging. 2011;20(1): doi: /

Date of download: 6/22/2016 Copyright © 2016 SPIE. All rights reserved. Segmentation results for a synthetic image from the proposed method: (a) initial contour, (b) final contour, (c) result derived from the JSEG method for comparison, (d) final contour (of the proposed method) under \documentclass[12pt]{minimal}\begin{document}$\rm {SNR}=40\, \rm {dB}$\end{document} SNR =40 dB, class number n = 10, (e) \documentclass[12pt]{minimal}\begin{document}$\rm {SNR}=40\, \rm {dB}$\end{document} SNR =40 dB, n = 20, (f) \documentclass[12pt]{minimal}\begin{document}$\rm {SNR}=26\, \rm {dB}$\end{document} SNR =26 dB, n = 20. Figure Legend: From: Image segmentation by optimizing a homogeneity measure in a variational framework J. Electron. Imaging. 2011;20(1): doi: /

Date of download: 6/22/2016 Copyright © 2016 SPIE. All rights reserved. Different segmentation results, all with small values of the inhomogeneity measure \documentclass[12pt]{minimal}\begin{document}$\skew6\bar{J}$\end{document}J¯. Figure Legend: From: Image segmentation by optimizing a homogeneity measure in a variational framework J. Electron. Imaging. 2011;20(1): doi: /

Date of download: 6/22/2016 Copyright © 2016 SPIE. All rights reserved. Flow chart of the proposed algorithm. Figure Legend: From: Image segmentation by optimizing a homogeneity measure in a variational framework J. Electron. Imaging. 2011;20(1): doi: /

Date of download: 6/22/2016 Copyright © 2016 SPIE. All rights reserved. Interim results derived by the proposed algorithm on an example image: (a) the original image; (b) the class map with n = 3, different gray level represents different class; (c) the initial contour depicted by the white line; (d) the contour in evolution; (e) the final segmentation result. Figure Legend: From: Image segmentation by optimizing a homogeneity measure in a variational framework J. Electron. Imaging. 2011;20(1): doi: /

Date of download: 6/22/2016 Copyright © 2016 SPIE. All rights reserved. Window for calculating the local value of the inhomogeneity measure J Figure Legend: From: Image segmentation by optimizing a homogeneity measure in a variational framework J. Electron. Imaging. 2011;20(1): doi: /

Date of download: 6/22/2016 Copyright © 2016 SPIE. All rights reserved. Enhancement on the calculation of the local J value. (a) Class map, (b) window around position A, (c) window around position B, (d) local J profile before enhancement, (e) local J profile after enhancement. Figure Legend: From: Image segmentation by optimizing a homogeneity measure in a variational framework J. Electron. Imaging. 2011;20(1): doi: /

Date of download: 6/22/2016 Copyright © 2016 SPIE. All rights reserved. Segmentation results for an image of two textured regions. (a) Initial contour; (b) final contour by the proposed algorithm; (c) final contour by the JSEG method. Figure Legend: From: Image segmentation by optimizing a homogeneity measure in a variational framework J. Electron. Imaging. 2011;20(1): doi: /

Date of download: 6/22/2016 Copyright © 2016 SPIE. All rights reserved. The resultant segmentation of two images composed of Brodatz textures. (a) and (b) Original images. (c) and (d) Segmentation results by the proposed algorithm. (e) and (f) Segmentation results by the JSEG method. Figure Legend: From: Image segmentation by optimizing a homogeneity measure in a variational framework J. Electron. Imaging. 2011;20(1): doi: /

Date of download: 6/22/2016 Copyright © 2016 SPIE. All rights reserved. Segmentation results on a set of real images. (a), (e), (i), (m) and (q) Original images. (b), (f), (j), (n) and (r) Segmentation results by the proposed algorithm. (c), (g), (k), (o) and (s) Segmentation results by the JSEG method. (d), (h), (l), (p) and (t) Segmentation results by the GVF snake method. Figure Legend: From: Image segmentation by optimizing a homogeneity measure in a variational framework J. Electron. Imaging. 2011;20(1): doi: /

Date of download: 6/22/2016 Copyright © 2016 SPIE. All rights reserved. Initial contour's setting in the experiments with the GVF snake method. Figure Legend: From: Image segmentation by optimizing a homogeneity measure in a variational framework J. Electron. Imaging. 2011;20(1): doi: /