Color Texture Image Segmentation Based on Neutrosophic Set and Nonsubsampled Contourlet Transformation

详细信息    查看全文

• 作者：Jeethu Mary Mathew (18)
  Philomina Simon (18)
  
• 关键词：Neutrosophic set ; Color Texture segmentation ; Nonsubsampled Contourlet Transform ; Fuzzy clustering
• 刊名：Lecture Notes in Computer Science
• 出版年：2014
• 出版时间：2014
• 年：2014
• 卷：8321
• 期：1
• 页码：164-173
• 全文大小：281 KB
• 参考文献：1. Gonzalez, R.C., Woods, R.E.: Digital image processing. Addison-Wesley (1992)
  2. Cheng, H.-D., Jiang, X., Sun, Y., Wang, J.: Color image segmentation: advances and prospects. Pattern Recognition聽34(12), 2259鈥?281 (2001) CrossRef
  3. Seng眉r, A.: Wavelet transform and adaptive neuro-fuzzy inference system for color texture classification. Expert Syst. Appl.聽34(3), 2120鈥?128 (2008) CrossRef
  4. Jung, C.R.: Unsupervised multiscale segmentation of color images. Pattern Recognition Letters聽28(4), 523鈥?33 (2007) CrossRef
  5. Ozden, M., Polat, E.: A color image segmentation approach for content-based image retrieval. Pattern Recognition聽40(4), 1318鈥?325 (2007) CrossRef
  6. Deng, Y., Manjunath, B.S.: Unsupervised segmentation of color-texture regions in images and video. IEEE Trans. Pattern Anal. Mach. Intell.聽23(8), 800鈥?10 (2001) CrossRef
  7. Kothainachiar, S., Wahita Banu, R.S.D.: A novel image segmentation based on a combination of colour and texture features. ICGST International Journal on Graphics, Vision and Image Processing, GVIP聽07, 45鈥?1 (2007)
  8. Garcia-Ugarriza, L., Saber, E., Vantaram, S.R., Amuso, V., Shaw, M., Bhaskar, R.: Automatic image segmentation by dynamic region growth and multiresolution merging. IEEE Transactions on Image Processing聽18(10), 2275鈥?288 (2009) CrossRef
  9. Li, S., Xu, J., Ren, J., Xu, T.: A color image segmentation algorithm by integrating watershed with region merging. In: Li, T., Nguyen, H.S., Wang, G., Grzymala-Busse, J., Janicki, R., Hassanien, A.E., Yu, H. (eds.) RSKT 2012. LNCS, vol.聽7414, pp. 167鈥?73. Springer, Heidelberg (2012) CrossRef
  10. An, N.-Y., Pun, C.-M.: Color image segmentation using adaptive color quantization and multiresolution texture characterization. Signal, Image and Video Processing, 1鈥?2
  11. Guo, Y., Cheng, H.D.: New neutrosophic approach to image segmentation. Pattern Recognition聽42(5), 587鈥?95 (2009) CrossRef
  12. Chen, J., Pappas, T.N., Mojsilovic, A., Rogowitz, B.: Image segmentation by spatially adaptive color and texture features. In: Proceedings of the 2003 International Conference on Image Processing, ICIP 2003, vol.聽1, p. I鈥?005鈥? (2003)
  13. Seng眉r, A., Guo, Y.: Color texture image segmentation based on neutrosophic set and wavelet transformation. Computer Vision and Image Understanding聽115(8), 1134鈥?144 (2011) CrossRef
  14. Smarandache, F.: A unifying field in logics: Neutrosophic logic. neutrosophy, neutrosophic set, neutrosophic probability and statistics, 4th edn. (2005)
  15. Wang, H., Smarandache, F., Zhang, Y.-Q., Sunderraman, R.: Interval neutrosophic sets and logic: Theory and applications in computing. CoRR (2005)
  16. Da Cunha, A.L., Zhou, J., Do, M.N.: The nonsubsampled contourlet transform: Theory, design, and applications. IEEE Transactions on Image Processing聽15(10), 3089鈥?101 (2006) CrossRef
  17. Blesslin Elizabeth, C.P., Usha, K., Devi, K.: Spectral clustering of images in luv color space by spatial-color pixel classification
  18. Bezdek, J.C., Ehrlich, R., Full, W.: Fcm: The fuzzy c-means clustering algorithm. Computers & Geosciences聽10(2-3), 191鈥?03 (1984) CrossRef
  19. Xie, X.L., Beni, G.: A validity measure for fuzzy clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence聽13(8), 841鈥?47 (1991) CrossRef
  20. Martin, D., Fowlkes, C., Tal, D., Malik, J.: A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics. In: Proc. 8th Int鈥檒 Conf. Computer Vision, vol.聽2, pp. 416鈥?23 (July 2001)
  21. Abdou, I.E., Pratt, W.: Quantitative design and evaluation of enhancement/thresholding edge detectors. Proceedings of the IEEE聽67(5), 753鈥?63 (1979) CrossRef
  22. Martin, D.R., Fowlkes, C.C., Malik, J.: Learning to detect natural image boundaries using local brightness, color, and texture cues. IEEE Trans. Pattern Anal. Mach. Intell.聽26(5), 530鈥?49 (2004) CrossRef
  
• 作者单位：Jeethu Mary Mathew (18)
  Philomina Simon (18)
  
  18. Department of Computer Science, University of Kerala, Kariavattom, Thiruvananthapuram, Kerala, India
  
• ISSN：1611-3349

文摘

In this paper, an automatic approach for image segmentation based on neutrosophic set and nonsubsampled contourlet transformation for natural images is proposed. This method uses both color and texture features for segmentation. Input image is transformed into LUV color model for extracting the color features. Texture features are extracted from the grayscale image. Image is then transformed into Neutrosophic domain. Finally, image segmentation is performed using Fuzzy C-means clustering. Clusters are adaptively calculated based on a cluster validity analysis. This method is tested in natural image database. The result analysis shows that the proposed method automatically segments image better than traditional methods.