Research on the image segmentation necessity for regions-based image processing

Information Technology Journal

Volumn 7, Issue 2, 2008, Pages 269-276

  Zhang, Mingxin ^a,b   Shang, Zhaowei ^c   Shen, Junyi ^a  

^a XI'AN JIAOTONG UNIVERSITY   (China)

^b LANZHOU UNIVERSITY OF TECHNOLOGY   (China)

^c CHONGQING UNIVERSITY   (China)

Author keywords

Complexity; Connectivity index; Image segmentation; Wavelet modulus maxima points

Indexed keywords

COMPUTATION THEORY; IMAGE ANALYSIS; PATTERN RECOGNITION;

CONNECTIVITY INDEX; WAVELET MODULUS MAXIMA POINTS;

IMAGE SEGMENTATION;

EID: 41549153305     PISSN: 18125638     EISSN: 18125646     Source Type: Journal    
DOI: 10.3923/itj.2008.269.276     Document Type: Article

References (15)

1. Chen, C.W., J. Luo and K.J. Parker, 1998. Image segmentation via adaptive K-mean clustering and knowledge-based morphological operations with biomedical applications. IEEE. Trans. Image Process., 7 (12): 1673-1683.
2. Chunming, L., X. Chenyang, G. Changfeng and M.D. Fox, 2005. Level set evolution without re-initialization: A new variational formulation. Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, San Diego, CA, USA.
3. Comaniciu, D. and P. Meer, 2002. Mean shift: A robust approach toward feature space analysis. IEEE. Trans. Pattern Anal. Mach. Intel., 24 (5): 603-619.
4. Dai, Z.K., L. HanQing, D. MiYi and Z. Qi, 2006. Automatic salient regions of interest extraction based on edge and region integration. Proceedings of IEEE International Symposium on Industrial Electronics, Montreal, Quebec, Canada.
5. Edward, R.D., 1993. Mathematical Morphology in Image Processing. M. Dekker, New York, USA.
6. Felzenszwalb, P.F. andD.P. Huttenlocher, 2004. Efficient graph-based image segmentation. Int. J. Comput. Vision, 59 (2): 167-181.
7. Fwu, J.K. and P.M. Djuric, 1997. EM algorithm for image segmentation initialized by a tree structure scheme. IEEE. Trans. Image Process., 6 (2): 349-352.
8. Haralick, R.M. and L.G. Shapiro, 1992. Computer and Robot Vision (Volume 1). Addison-Wesley, Massachusetts, USA.
9. Jianbo, S. and J. Malik, 2000. Normalized cuts and image segmentation. IEEE. Trans. Pattern Anal. Mach. Intel., 22 (8): 888-905.
10. Larrabide, I., R.A. Feij, E. Taroco and A. Novotny, 2006. Configurational derivative as a tool for image segmentation. Proceedings of the ECCM 2006, Lisbon, Portugal.
11. Luo, Y., Y.J. Zhang, Y.Y. Gao and W.P. Yang, 2001. Extracting meaningful region for content-based retrieval of image and video. Proceedings of SPIE., 4310: 455-464.
12. Mallat, S. and W.L. Hwang, 1992. Singularity detection and processing with wavelets. IEEE. Trans. Inform. Theor., 38 (2): 617-643.
13. Montoya, M.D.G., C. Gil and I. Garcia, 1999. Load balancing for a class of irregular and dynamic problems: Region growing image segmentation algorithms. Proceedings of the 7th Euromicro Workshop on Parallel and Distributed Processing, Funchal, Portugal.
14. Shao, L., T. Kadir and M. Brady, 2007. Geometric and photometric invariant distinctive regions detection. Inform. Sci., 177(4): 1088-1122.
15. Xue, D.Y. and V. Gupta, 1993. An improved threshold selection method for image segmentation. Proceedings of Canadian Conference on Electrical and Computer Engineering, Vancouver, Canada.