Mô Hình Hiệu Suất và Đặc Trưng Thuật Toán cho Phân Đoạn Hình Ảnh Đáng Tin Cậy

Borsotti, M., Campadelli, P., & Schettini, R. (1998). Quantitative evaluation of color image segmentation results. Pattern Recognition Letters, 19, 741–747. Brox, T., & Weickert, J. (2004). Level set based image segmentation with multiple regions. In LNCS : Vol. 3175. Pattern recognition (pp. 415–423). Berlin: Springer. Chalmond, B., Graffigne, C., Prenat, M., & Roux, M. (2001). Contextual performance prediction for low-level image analysis algorithms. IEEE Transactions on Image Processing, 10, 1039–1046. Chiang, H. C., & Moses, R. L. (1999). ATR performance prediction using attributed scattering features. In Proceedings of SPIE (Vol. 3721, pp. 785–796). Bellingham: SPIE. Chiang, H. C., Moses, R. L., & Potter, L. C. (2000). Classification performance prediction using parametric scattering feature models. In Proceedings of SPIE (Vol. 4053, pp. 7546–557). Bellingham: SPIE. Cho, K., Meer, P., & Cabrera, J. (1997). Performance assessment through bootstrap. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19, 1185–1198. Comaniciu, D., & Meer, P. (2002). Mean shift: A robust approach toward feature space analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24, 603–619. Duda, R. O., & Hart, P. E. (1973). Pattern classification and scene analysis. New York: Wiley-Interscience. Ettinger, G. J., Klanderman, G. A., Wells, W. M., & Grimson, W. E. L. (1996). Probabilistic optimization approach to SAR feature matching. In Proceedings of SPIE (Vol. 2757, pp. 318–329). Bellingham: SPIE. Felzenszwalb, P., & Huttenlocher, D. (2004). Efficient graph-based image segmentation. International Journal of Computer Vision, 59, 167–181. Fogel, I., & Sagi, D. (1989). Gabor filters as texture discriminator. Biological Cybernetics, 61, 103–113. Freixenet, J., Munoz, X., Raba, D., Marti, J., & Cufi, X. (2002). Yet another survey on image segmentation: Region and boundary information integration. In ECCV’02: Proceedings of the 7th European conference on computer vision—Part III (pp. 408–422). London: Springer. Fu, K., & Mui, J. (1981). A survey on image segmentation. Pattern Recognition, 13, 3–16. Haralick, R. M., & Shapiro, L. G. (1992). In Computer and robot vision (Vol. 1, pp. 303–370). Reading: Addison-Wesley. Konishi, S., & Yuille, A. L. (2000). Statistical cues for domain specific image segmentation with performance analysis. In IEEE computer vision and pattern recognition or CVPR I (pp. 125–132). Laws, K. I. (1980). Textured image segmentation. Ph.D. thesis. Liu, J., & Yang, Y. H. (1994). Multiresolution color image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 16, 689–700. Martin, D. R., Fowlkes, C. C., Tal, D., & Malik, J. (2001). A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics. In International conference on computer vision II (pp. 416–423). Meila, M. (2005). Comparing clusterings: an axiomatic view. In ICML’05: Proceedings of the 22nd international conference on machine learning (pp. 577–584). New York: Assoc. Comput. Mach. Nair, D., & Aggarwal, J. K. (1996). A focused target segmentation paradigm. In Fourth European conference on computer vision (Vol. 1, pp. 579–588). Berlin: Springer. Pal, N. R., & Pal, S. K. (1993). A review on image segmentation techniques. Pattern Recognition, 26, 1277–1294. Pavlidis, T. (1977). Structural pattern recognition. Berlin: Springer. Perner, P. (1999). An architecture for a CBR image segmentation system. In ICCBR’99: Proceedings of the third international conference on case-based reasoning and development (pp. 525–534). Berlin: Springer. Puzicha, J., Hofmann, T., & Buhmann, J. M. (1999). Histogram clustering for unsupervised segmentation and image retrieval. Pattern Recognition Letters, 20, 899–909. Randen, T., & Husoy, J. H. (1999). Filtering for texture classification: A comparative study. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21, 291–310. Ren, X., & Malik, J. (2003). Learning a classification model for segmentation. In International conference on computer vision (pp. 10–17). Reynolds, R. G., & Rolnick, S. R. (1995). Learning the parameters for a gradient-based approach to image segmentation using cultural algorithms. In Proceedings of the first international symposium on intelligence in neural and biological systems (INBS’95) (Vol. 240). Los Alamitos: IEEE Comput. Soc. Shi, J., & Malik, J. (2000). Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22, 888–905. Shufelt, J. A. (1999). Performance evaluation and analysis of monocular building extraction from aerial imagery. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21, 311–326. Spann, M., & Nieminen, A. (1988). Adaptive Gaussian weighted filtering for image segmentation. Pattern Recognition Letters, 8, 251–255. Spann, M., & Grace, A. (1994). Adaptive segmentation of noisy and textured images. Pattern Recognition, 27, 1717–1733. Tourassi, G. D., Frederick, E. D., Vittitoe, N. F., & Coleman, R. E. (2000). Fractal texture analysis of perfusion lung scans. Computers in Biomedical Research, 33, 161–171. Tuceryan, M., & Jain, A. K. (1993). Texture analysis. Handbook of Pattern Recognition and Computer Vision, 235–276. van Rijsbergen, C. J. (1979). Information retrieval (2nd ed.). London: Butterworths. Yang, A. Y., Wright, J., Sastry, S. S., & Ma, Y. (2006). Unsupervised segmentation of natural images via lossy data compression (Technical Report UCB/EECS-2006-195). EECS Department, University of California, Berkeley. Zhang, Y. J. (1996). A survey on evaluation methods for image segmentation. Pattern Recognition, 29, 1335–1346. Zhang, X., & Haralick, R. M. (1993). Bayesian corner detection. In British machine vision conference. Zhang, H., Cholleti, S., Goldman, S. A., & Fritts, J. E. (2006). Meta-evaluation of image segmentation using machine learning. In IEEE conference on computer vision and pattern recognition I (pp. 1138–1145).