[1] سیدمحمدرضا موسوی، امیر باوفا طوسی، ":GCOCR روشی برای تشخیص حروف براساس شبکههای دروازهدار کانولوشنی و بازگشتی"، مجله علمی-پژوهشی رایانش نرم و فنآوری اطلاعات، جلد 13، شماره 3، پائیز 1403، صفحه 31-45.
[2] R.C. Gonzalez, R.E. Woods, S.L. Eddins, "Digital Image Processing Using MATLAB", Prentice Hall, Upper Saddle River, 2004. Available:https://www.google.de/books/edition/Digital_Image_Processing_Using_MATLAB/5YEMp6HjvnQC?hl=fa
[3] F. Kulwa, C. Li, X. Zhao, B. Cai, N. Xu, S. Qi, S. Chen, Y. Teng, "A state-of-the-art survey for microorganism image segmentation methods and future potential", IEEE Access, vol. 7, pp. 100243–100269, 2019. https://doi.org/10.1109/ACCESS.2019.2930111
[4] H. Digabel, C. Lantuejoul, "Iterative algorithms", Proceedings of the Second European Symposium on Quantitative Analysis of Microstructures in Materials Science, Biology, and Medicine, Université de Caen, France, Oct. 4–7, 1977. Available at: https://people.cmm.minesparis.psl.eu/users/marcoteg/cv/publi_pdf/MM_refs/Lantuejoul/1977_lantu_iterativeAlgorithms.pdf
[5] F. Meyer, "Un algorithme optimal de ligne de partage des eaux", Actes du 2, pp. 847-859, 1991. https://doi.org/10.1016/1047-3203(90)90014-M
[6] T. Lei, X. Jia, T. Liu, S. Liu, H. Meng, A.K. Nandi, "Adaptive morphological reconstruction for seeded image segmentation", IEEE Transactions on Image Processing, vol. 28, no. 11, pp. 5510–5523, 2019. https://doi.org/10.1109/TIP.2019.2920514
[7] R. Gaetano, G. Masi, G. Poggi, L. Verdoliva, G. Scarpa, "Marker-controlled watershed-based segmentation of multiresolution remote sensing images", IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 6, pp. 2987–3004, 2015. https://doi.org/10.1109/TGRS.2014.2367129
[8] A. Kucharski, A. Fabijańska, "CNN-watershed: A watershed transform with predicted markers for corneal endothelium image segmentation", Biomedical Signal Processing and Control, vol. 68, p. 102805, 2021. https://doi.org/10.1016/j.bspc.2021.102805
[9] Y. Chen, H. Du, Z. Yun, S. Yang, Z. Dai, L. Zhong, Q. Feng, W. Yang, "Automatic segmentation of individual tooth in dental CBCT images from tooth surface map by a multi-task FCN", IEEE Access, vol. 8, pp. 97296–97309, 2020. https://doi.org/10.1109/ACCESS.2020.2991799
[10] P. Prabhu, K.A. Kotegar, N. Mariyappa, H. Anitha, G.K. Bhargava, J. Saini, S. Sinha, "Segmentation of Temporomandibular Condyle in MR images using Marker-Controlled Watershed and Random Walks", Proceedings of the 2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC), pp. 01-05, 2021. https://doi.org/10.1109/R10-HTC53172.2021.9641714
[11] T. Indriyani, M. Utoyo, R. Rulaningtyas, "A new watershed algorithm for pothole image segmentation", Stud. Inform. Control, vol. 30, no. 3, 2021. https://doi.org/10.24846/v30i3y202112
[12] H. Xu, M. Langer, F. Peyrin, "Quantitative analysis of bone microvasculature in a mouse model using the monogenic signal phase asymmetry and marker-controlled watershed", Physics in Medicine & Biology, vol. 66, no. 12, p. 125005, 2021. https://doi.org/10.1088/1361-6560/ac047d
[13] X. Wang, S. Wan, T. Lei, "Brain Tumor Segmentation Based on Structuring Element Map Modification and Marker-controlled Watershed Transform", Journal of Software, vol. 9, no. 11, pp. 2925–2932, 2014. https://doi.org/10.4304/JSW.9.11.2925-2932
[14] M. R. M. Razali, N. S. Ahmad, W. Ismail, "Dental age assessment for forensic identification using OTSU and watershed algorithm", Proceedings of the International Conference on Advances in Computing and Information Technology (ACIT), pp. 134–138, 2014.
[15] K. Devaki, V.M. Bhaskaran, "A novel approach to detect fissures in lung CT images using marker-based watershed transformation", Journal of Computer Science, vol. 10, no. 6, pp. 896–905, 2014. https://doi.org/10.3844/jcssp.2014.896.905
[16] T.D. Chung, M.A. Khan, "Watershed-based real-time image processing for multi-potholes detection on asphalt road", Proceedings of the 2019 IEEE 9th International Conference on System Engineering and Technology (ICSET), pp. 268–272, October 2019. https://doi.org/10.1109/ICSEngT.2019.8906371
[17] U.S. Khan, Z. Liu, F. Xu, M.U. Khan, L. Chen, T.A. Khan, M.K. Khattak, Y. Zhang, "Unsupervised Color Segmentation with Reconstructed Spatial Weighted Gaussian Mixture Model and Random Color Histogram", Computers, Materials and Continua, vol. 78, pp. 3323–3348, 2024. https://doi.org/10.32604/cmc.2024.046094
[18] T. Lei, X. Jia, Y. Zhang, L. He, H. Meng, A.K. Nandi, "Significantly fast and robust fuzzy c-means clustering algorithm based on morphological reconstruction and membership filtering", IEEE Transactions on Fuzzy Systems, vol. 26, no. 5, pp. 3027–3041, 2018. https://doi.org/10.1109/TFUZZ.2018.2796074
[19] T. Lei, P. Liu, X. Jia, X. Zhang, H. Meng, A.K. Nandi, "Automatic fuzzy clustering framework for image segmentation", IEEE Transactions on Fuzzy Systems, vol. 28, no. 9, pp. 2078–2092, 2020. https://doi.org/10.1109/TFUZZ.2019.2930030
[20] B. Ji, X. Hu, F. Ding, Y. Ji, H. Gao, "An effective color image segmentation approach using superpixel-neutrosophic C-means clustering and gradient-structural similarity", Optik, vol. 260, p. 169039, 2022. https://doi.org/10.1016/j.ijleo.2022.169039
[21] J. Jiao, X. Wang, T. Wei, J. Zhang, "An adaptive fuzzy c-means noise image segmentation algorithm combining local and regional information", IEEE Transactions on Fuzzy Systems, vol. 31, no. 8, pp. 2645–2657, 2023. https://doi.org/10.1109/TFUZZ.2023.3235392
[22] P. Arbeláez, M. Maire, C. Fowlkes, J. Malik, "Contour detection and hierarchical image segmentation", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 33, no. 5, pp. 898–916, 2011. https://doi.org/10.1109/TPAMI.2010.161
[23] P. Dollár, C.L. Zitnick, "Fast edge detection using structured forests", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 37, no. 8, pp. 1558–1570, 2015. https://doi.org/10.1109/TPAMI.2014.2377715
[24] S. Hallman, C.C. Fowlkes, "Oriented edge forests for boundary detection", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1732–1740, June 7–12, 2015. https://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Hallman_Oriented_Edge_Forests_2015_CVPR_paper.pdf
[25] P. Soille, "Morphological Image Analysis: Principles and Applications, 2nd edition", Springer, 2002. https://doi.org/10.1007/978-3-662-05088-0
[26] A. Y. Yang, J. Wright, Y.Ma, S.S. Sastry, "Unsupervised segmentation of natural images via lossy data compression", Computer Vision and Image Understanding, vol. 110, no. 2, pp. 212-225, 2008. https://doi.org/10.1016/j.cviu.2007.07.005
[27] R. Unnikrishnan, C. Pantofaru, M. Hebert, "Toward objective evaluation of image segmentation algorithms", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 6, pp. 929–944, 2007. https://doi.org/10.1109/TPAMI.2007.1046
[28] C. Fowlkes, D. Martin, J. Malik, "Learning affinity functions for image segmentation: Combining patch-based and gradient-based approaches", Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), vol. 2, pp. II-54, June 2003. https://doi.org/10.1109/CVPR.2003.1211452
[29] D. Khosla, R. Uhlenbroch, Y. Chen, "Automated scene understanding via fusion of image and object features", Proceedings of 2017 IEEE International Symposium on Technologies for Homeland Security (HST), pp. 1-4, 2017. https://doi.org/10.1109/THS.2017.7943474
[30] T. Malisiewicz, A.A. Efros, "Improving spatial support for objects via multiple segmentations", Proceedings of BMVC 2007 – Proceedings of the British Machine Vision Conference 2007, pp. 1-8, 2007. Available: https://bmva-archive.org.uk/bmvc/2007/papers/paper-304.pdf
[32] A. Farooq, K.H. Memon, “Kernel possibilistic fuzzy c-means clustering algorithm based on morphological reconstruction and membership filtering”, Fuzzy Sets and Systems, vol.477, p.108792,2024. DOI: https://doi.org/10.1016/j.fss.2023.108792
