Image segmentation evaluation: a survey of methods
暂无分享,去创建一个
Ying Zhu | Zhaobin Wang | E. Wang | Zhaobin Wang | Ying Zhu | E. Wang
[1] Evgin Göçeri,et al. Challenges and Recent Solutions for Image Segmentation in the Era of Deep Learning , 2019 .
[2] Ying Liu,et al. Unsupervised Segmentation Evaluation Using Area-Weighted Variance and Jeffries-Matusita Distance for Remote Sensing Images , 2018, Remote. Sens..
[3] Raveendran Paramesran,et al. Visual Quality Evaluation of Image Object Segmentation: Subjective Assessment and Objective Measure , 2015, IEEE Transactions on Image Processing.
[4] Theo van Walsum,et al. An Evaluation of CNN-based Liver Segmentation Methods using Multi-types of CT Abdominal Images from Multiple Medical Centers , 2019, 2019 19th International Symposium on Communications and Information Technologies (ISCIT).
[5] Touradj Ebrahimi,et al. MESH: measuring errors between surfaces using the Hausdorff distance , 2002, Proceedings. IEEE International Conference on Multimedia and Expo.
[6] Uday Pratap Singh,et al. Soft computing approaches for image segmentation: a survey , 2018, Multimedia Tools and Applications.
[7] Evgin Goceri,et al. Computer-based segmentation, change detection and quantification for lesions in multiple sclerosis , 2017, 2017 International Conference on Computer Science and Engineering (UBMK).
[8] Olga Kubassova,et al. General framework for unsupervised evaluation of quality of segmentation results , 2008, 2008 15th IEEE International Conference on Image Processing.
[9] Hui Zhang,et al. Image segmentation evaluation: A survey of unsupervised methods , 2008, Comput. Vis. Image Underst..
[10] Shengwei Zhang,et al. Local and global evaluation for remote sensing image segmentation , 2017 .
[11] Peijun Li,et al. Evaluation of multiscale morphological segmentation of multispectral imagery for land cover classification , 2004, IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium.
[12] Subrata Rakshit,et al. Statistical evaluation of image segmentation , 2010, 2010 IEEE 2nd International Advance Computing Conference (IACC).
[13] Zhaoquan Cai,et al. Unsupervised segmentation evaluation: an edge-based method , 2016, Multimedia Tools and Applications.
[14] Evgin Goceri,et al. Vessel segmentation from abdominal magnetic resonance images: adaptive and reconstructive approach , 2016, International journal for numerical methods in biomedical engineering.
[15] Nilanjan Dey,et al. Social Group Optimization Supported Segmentation and Evaluation of Skin Melanoma Images , 2018, Symmetry.
[16] Jan J. Gerbrands,et al. Three-dimensional image segmentation using a split, merge and group approach , 1991, Pattern Recognit. Lett..
[17] Yong Dou,et al. Aircraft Segmentation from Remote Sensing Image by Transferring Natual Image Trained Forground Extraction CNN Model , 2019, 2019 IEEE 4th International Conference on Signal and Image Processing (ICSIP).
[18] Dinggang Shen,et al. High-Resolution Encoder–Decoder Networks for Low-Contrast Medical Image Segmentation , 2020, IEEE Transactions on Image Processing.
[19] Amir Alansary,et al. MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans , 2015, Comput. Intell. Neurosci..
[20] Lei Zhang,et al. Evaluation of Segmentation Quality via Adaptive Composition of Reference Segmentations , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[21] Thomas Wittenberg,et al. Using simulated fluorescence cell micrographs for the evaluation of cell image segmentation algorithms , 2017, BMC Bioinformatics.
[22] Marjan Abdechiri,et al. An unsupervised evaluation method based on probability density function , 2010, 2010 IEEE International Symposium on Industrial Electronics.
[23] Christophe Rosenberger,et al. Genetic fusion: application to multi-components image segmentation , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).
[24] Hélène Laurent,et al. Unsupervised evaluation of image segmentation application to multi-spectral images , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..
[25] D. Ming,et al. Review on High Spatial Resolution Remote Sensing Image Segmentation Evaluation , 2018, Photogrammetric Engineering & Remote Sensing.
[26] Nina Sumiko Tomita Hirata,et al. Image Segmentation Assessment from the Perspective of a Higher Level Task , 2015, 2015 28th SIBGRAPI Conference on Graphics, Patterns and Images.
[27] José Hiroki Saito,et al. NSGA2-based method for band selection for supervised segmentation in hyperspectral imaging , 2019, 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC).
[28] Hui Zhang,et al. An entropy-based objective evaluation method for image segmentation , 2003, IS&T/SPIE Electronic Imaging.
[29] Evgin Goceri,et al. Automated detection and extraction of skull from MR head images: Preliminary results , 2017, 2017 International Conference on Computer Science and Engineering (UBMK).
[30] Jesmin F. Khan,et al. Weighted entropy for segmentation evaluation , 2014 .
[31] Juan Domingo,et al. Iteratively Learning a Liver Segmentation Using Probabilistic Atlases: Preliminary Results , 2016, 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA).
[32] Bo Peng,et al. A Probabilistic Measure for Quantitative Evaluation of Image Segmentation , 2013, IEEE Signal Processing Letters.
[33] Jian Yang,et al. A multi-band approach to unsupervised scale parameter selection for multi-scale image segmentation , 2014 .
[34] Nikos Komodakis,et al. Learning to compare image patches via convolutional neural networks , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[35] Allan Hanbury,et al. A formal method for selecting evaluation metrics for image segmentation , 2014, 2014 IEEE International Conference on Image Processing (ICIP).
[36] Andrea Vedaldi,et al. MatConvNet: Convolutional Neural Networks for MATLAB , 2014, ACM Multimedia.
[37] Evgin Göçeri,et al. Automatic labeling of portal and hepatic veins from MR images prior to liver transplantation , 2016, Int. J. Comput. Assist. Radiol. Surg..
[38] Tang Zhaohui,et al. An unsupervised method for flotation froth image segmentation evaluation base on image gray-level distribution , 2013, Proceedings of the 32nd Chinese Control Conference.
[39] Jian Yang,et al. A discrepancy measure for segmentation evaluation from the perspective of object recognition , 2015 .
[40] Allan Hanbury,et al. Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool , 2015, BMC Medical Imaging.
[41] Evgin Göçeri,et al. Artificial Neural Network Based Abdominal Organ Segmentations: A Review , 2015, 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA).
[42] Ronghua Shang,et al. Densely Based Multi-Scale and Multi-Modal Fully Convolutional Networks for High-Resolution Remote-Sensing Image Semantic Segmentation , 2019, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[43] Zhenzhong Chen,et al. Visual Quality Evaluation for Semantic Segmentation: Subjective Assessment Database and Objective Assessment Measure , 2019, IEEE Transactions on Image Processing.
[44] Pengfei Shan,et al. Image segmentation method based on K-mean algorithm , 2018, EURASIP Journal on Image and Video Processing.
[45] Wiro Niessen,et al. Quantitative evaluation of noise reduction and vesselness filters for liver vessel segmentation on abdominal CTA images , 2015, Physics in medicine and biology.
[46] Y. J. Zhang,et al. A survey on evaluation methods for image segmentation , 1996, Pattern Recognit..
[47] Nikhil R. Pal,et al. Image thresholding: Some new techniques , 1993, Signal Process..
[48] Gang Li,et al. Scale-constrained unsupervised evaluation method for multi-scale image segmentation , 2016, 2016 IEEE International Conference on Image Processing (ICIP).
[49] Barbara Zitová,et al. Performance evaluation of image segmentation algorithms on microscopic image data , 2015, Journal of microscopy.
[50] Farid García,et al. Segmentation of images by color features: A survey , 2018, Neurocomputing.
[51] Tepán Rubar. Quality Measurement of Image Segmentation Evaluation Methods , 2012, SITIS.
[52] Xiaoli Zhang,et al. A weighted-ROC graph based metric for image segmentation evaluation , 2016, Signal Process..
[53] Alfredo Illanes,et al. Evaluation of Commonly Used Algorithms for Thyroid Ultrasound Images Segmentation and Improvement Using Machine Learning Approaches , 2018, Journal of healthcare engineering.
[54] Bo Peng,et al. Region Based Exemplar References for Image Segmentation Evaluation , 2016, IEEE Signal Processing Letters.
[55] Jesmin Khan,et al. Evaluation of the number of segments using weighted entropy , 2011, 2011 IEEE 43rd Southeastern Symposium on System Theory.
[56] Oleh Pitsun,et al. Regions matching algorithms analysis to quantify the image segmentation results , 2016, 2016 XIth International Scientific and Technical Conference Computer Sciences and Information Technologies (CSIT).
[57] Brian Johnson,et al. Unsupervised image segmentation evaluation and refinement using a multi-scale approach , 2011 .
[58] Roberto de Alencar Lotufo,et al. Benchmark for Quantitative Evaluation of Assisted Object Segmentation Methods to Image Sequences , 2008, 2008 XXI Brazilian Symposium on Computer Graphics and Image Processing.
[59] Jeffrey J. Rodriguez,et al. A Ground-Truth Fusion Method for Image Segmentation Evaluation , 2018, 2018 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI).
[60] Jocelyn Chanussot,et al. Dynamic Multicontext Segmentation of Remote Sensing Images Based on Convolutional Networks , 2018, IEEE Transactions on Geoscience and Remote Sensing.
[61] C. Mala,et al. Analysis and performance evaluation of various image segmentation methods , 2014, 2014 International Conference on Contemporary Computing and Informatics (IC3I).
[62] Martin D. Levine,et al. Dynamic Measurement of Computer Generated Image Segmentations , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[63] Evgin Goceri,et al. Challenges and Recent Solutions for Image Segmentation in the Era of Deep Learning , 2019, 2019 Ninth International Conference on Image Processing Theory, Tools and Applications (IPTA).
[64] Qingbo Wu,et al. Segmentation quality evaluation based on multi-scale convolutional neural networks , 2017, 2017 IEEE Visual Communications and Image Processing (VCIP).
[65] Hossam Faris,et al. An efficient clustering algorithm based on the k-nearest neighbors with an indexing ratio , 2019, International Journal of Machine Learning and Cybernetics.
[66] Yongji Wang,et al. Hybrid Remote Sensing Image Segmentation Considering Intrasegment Homogeneity and Intersegment Heterogeneity , 2020, IEEE Geoscience and Remote Sensing Letters.
[67] M. Neubert,et al. Enhanced evaluation of image segmentation results , 2010 .
[68] R Aarthi,et al. Segmentation and Evaluation of White Blood Cells using Segmentation Algorithms , 2019, 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI).
[69] Shamik Sural,et al. Evaluation of segmentation techniques using region area and boundary matching information , 2012, J. Vis. Commun. Image Represent..
[70] David Emms,et al. Fuzzy Evaluations of Image Segmentations , 2018, IEEE Transactions on Fuzzy Systems.
[71] P.K Sahoo,et al. A survey of thresholding techniques , 1988, Comput. Vis. Graph. Image Process..
[72] Elli Angelopoulou,et al. Supervised multispectral image segmentation with power watersheds , 2012, 2012 19th IEEE International Conference on Image Processing.
[73] Martial Hebert,et al. Toward Objective Evaluation of Image Segmentation Algorithms , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[74] José Martínez-Aroza,et al. A measure of quality for evaluating methods of segmentation and edge detection , 2001, Pattern Recognit..
[75] Xin Yang,et al. Joint Segment-Level and Pixel-Wise Losses for Deep Learning Based Retinal Vessel Segmentation , 2018, IEEE Transactions on Biomedical Engineering.
[76] Song Wang,et al. Image-Segmentation Evaluation From the Perspective of Salient Object Extraction , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[77] Hui Zhang,et al. Meta-Evaluation of Image Segmentation Using Machine Learning , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[78] Horst Bunke,et al. Distance Measures for Image Segmentation Evaluation , 2006, EURASIP J. Adv. Signal Process..
[79] Woei-Chyn Chu,et al. Performance measure characterization for evaluating neuroimage segmentation algorithms , 2009, NeuroImage.
[80] M. Gurcan,et al. Automated fluorescent miscroscopic image analysis of PTBP1 expression in glioma , 2017, PloS one.
[81] Frans Coenen,et al. Face Occlusion Detection Using Deep Convolutional Neural Networks , 2016, Int. J. Pattern Recognit. Artif. Intell..
[82] Jaime S. Cardoso,et al. Toward a generic evaluation of image segmentation , 2005, IEEE Transactions on Image Processing.
[83] Jayaram K. Udupa,et al. A critical analysis of the methods of evaluating MRI brain segmentation algorithms , 2017, 2017 IEEE International Conference on Image Processing (ICIP).
[84] Reza Ehsani,et al. Applications of High-Resolution Imaging for Open Field Container Nursery Counting , 2018, Remote. Sens..
[85] J. Satheesh Kumar,et al. Performance Evaluation of Image Segmentation using Objective Methods , 2016 .
[86] Evgin Goceri,et al. Diagnosis of Alzheimer's disease with Sobolev gradient‐based optimization and 3D convolutional neural network , 2019, International journal for numerical methods in biomedical engineering.
[87] Carsten Rother,et al. Panoptic Segmentation , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[88] David S. Doermann,et al. Unsupervised feature learning framework for no-reference image quality assessment , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[89] Evgin Goceri,et al. A comparative performance evaluation of various approaches for liver segmentation from SPIR images , 2015 .
[90] Chen Wang,et al. Standardized Evaluation System for Left Ventricular Segmentation Algorithms in 3D Echocardiography , 2016, IEEE Transactions on Medical Imaging.
[91] Sheng-Jyh Wang,et al. The use of visible color difference in the quantitative evaluation of color image segmentation , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[92] Jocelyn Chanussot,et al. Multiscale stochastic watershed for unsupervised hyperspectral image segmentation , 2009, 2009 IEEE International Geoscience and Remote Sensing Symposium.
[93] Jordi Pont-Tuset,et al. Supervised Evaluation of Image Segmentation and Object Proposal Techniques , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[94] Haitao Zhang,et al. Color Space Transformation and Multi-Class Weighted Loss for Adhesive White Blood Cell Segmentation , 2020, IEEE Access.
[95] Clement Atzberger,et al. On the Objectivity of the Objective Function - Problems with Unsupervised Segmentation Evaluation Based on Global Score and a Possible Remedy , 2017, Remote. Sens..
[96] Aoxue Li,et al. Global and Local Saliency Analysis for the Extraction of Residential Areas in High-Spatial-Resolution Remote Sensing Image , 2016, IEEE Transactions on Geoscience and Remote Sensing.
[97] Xu Liu,et al. An End-To-End Network for Panoptic Segmentation , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[98] Xiaoqian Jiang,et al. Flexible methods for segmentation evaluation: results from CT-based luggage screening. , 2014, Journal of X-ray science and technology.
[99] Thierry Cresson,et al. A multi-criteria evaluation platform for segmentation algorithms , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[100] Evgin Göçeri,et al. A comparative evaluation for liver segmentation from spir images and a novel level set method using signed pressure force function , 2013 .
[101] Yessenia Yari,et al. Multispectral images segmentation using fuzzy probabilistic local cluster for unsupervised clustering , 2017, 2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI).
[102] Weiping Ni,et al. Optimal Segmentation Scale Selection for Object-Based Change Detection in Remote Sensing Images Using Kullback–Leibler Divergence , 2020, IEEE Geoscience and Remote Sensing Letters.
[103] King Ngi Ngan,et al. Objectness based unsupervised object segmentation quality evaluation , 2017, 2017 Seventh International Conference on Information Science and Technology (ICIST).
[104] Vittorio Ferrari,et al. End-to-End Training of Object Class Detectors for Mean Average Precision , 2016, ACCV.
[105] Bo Peng,et al. Region-based image segmentation evaluation via perceptual pooling strategies , 2017, Machine Vision and Applications.
[106] José-Fernán Martínez,et al. Fast Evaluation of Segmentation Quality with Parallel Computing , 2017, Sci. Program..
[107] Evgin Goceri,et al. Analysis of Deep Networks with Residual Blocks and Different Activation Functions: Classification of Skin Diseases , 2019, 2019 Ninth International Conference on Image Processing Theory, Tools and Applications (IPTA).
[108] Xueliang Zhang,et al. Segmentation quality evaluation using region-based precision and recall measures for remote sensing images , 2015 .
[109] S. Pare,et al. Image Segmentation Using Multilevel Thresholding: A Research Review , 2019, Iranian Journal of Science and Technology, Transactions of Electrical Engineering.
[110] King Ngi Ngan,et al. Jaccard index compensation for object segmentation evaluation , 2014, 2014 IEEE International Conference on Image Processing (ICIP).
[111] Xinran Lv,et al. Hierarchical Weakly Supervised Learning for Residential Area Semantic Segmentation in Remote Sensing Images , 2020, IEEE Geoscience and Remote Sensing Letters.
[112] Yee-Hong Yang,et al. Multiresolution Color Image Segmentation , 1994, IEEE Trans. Pattern Anal. Mach. Intell..
[113] Younes Jabrane,et al. A novel Gini index based evaluation criterion for image segmentation , 2018, Optik.
[114] Xuezhi Feng,et al. An Unsupervised Evaluation Method for Remotely Sensed Imagery Segmentation , 2012, IEEE Geoscience and Remote Sensing Letters.
[115] Chao Huang,et al. QualityNet: Segmentation quality evaluation with deep convolutional networks , 2016, 2016 Visual Communications and Image Processing (VCIP).
[116] Liaoying Zhao,et al. Different Versions of Entropy Rate Superpixel Segmentation For Hyperspectral Image , 2019, 2019 IEEE 4th International Conference on Signal and Image Processing (ICSIP).
[117] Mohcine Bouksim,et al. New evaluation method using sampling theory to evaluate 3D segmentation algorithms , 2016, 2016 4th IEEE International Colloquium on Information Science and Technology (CiSt).
[118] Jayaram K. Udupa,et al. A General and Balanced Region-Based Metric for Evaluating Medical Image Segmentation Algorithms , 2019, 2019 IEEE International Conference on Image Processing (ICIP).
[119] Stépan Srubar. Quality Measurement of Image Segmentation Evaluation Methods , 2012, 2012 Eighth International Conference on Signal Image Technology and Internet Based Systems.
[120] Jacek Jakubowski,et al. LEFMIS: locally-oriented evaluation framework for medical image segmentation algorithms , 2018, Physics in medicine and biology.
[121] Jordi Pont-Tuset,et al. Measures and Meta-Measures for the Supervised Evaluation of Image Segmentation , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[122] Haibo He,et al. A visual long-short-term memory based integrated CNN model for fabric defect image classification , 2020, Neurocomputing.
[123] Hui Li,et al. A Novel Unsupervised Segmentation Quality Evaluation Method for Remote Sensing Images , 2017, Sensors.
[124] Arjan Kuijper,et al. Extended surface distance for local evaluation of 3D medical image segmentations , 2015, The Visual Computer.
[125] Paola Campadelli,et al. Quantitative evaluation of color image segmentation results , 1998, Pattern Recognit. Lett..
[126] Libao Zhang,et al. Region-of-Interest Extraction Based on Frequency Domain Analysis and Salient Region Detection for Remote Sensing Image , 2014, IEEE Geoscience and Remote Sensing Letters.
[127] Asheesh Kumar Gautam,et al. Performance evaluation of Hyperspectral image segmentation implemented by recombination of PCT and Bilateral filter based fused images , 2016, 2016 3rd International Conference on Signal Processing and Integrated Networks (SPIN).
[128] Daniel Rueckert,et al. Patch-Based Evaluation of Image Segmentation , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[129] Patrik Kamencay,et al. Simple comparison of image segmentation algorithms based on evaluation criterion , 2011, Proceedings of 21st International Conference Radioelektronika 2011.
[130] Sylvie Philipp-Foliguet,et al. New Criteria for Evaluating Image Segmentation Results , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.
[131] Fernando Pereira,et al. Objective evaluation of video segmentation quality , 2003, IEEE Trans. Image Process..
[132] Tengfei Su. AN IMPROVED UNSUPERVISED IMAGE SEGMENTATION EVALUATION APPROACH BASED ON UNDER- AND OVER-SEGMENTATION AWARE , 2018 .
[133] Evgin Göçeri,et al. A Neural Network Based Kidney Segmentation from MR Images , 2015, 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA).
[134] David Zhang,et al. A comparative study on quality assessment of high resolution fingerprint images , 2010, 2010 IEEE International Conference on Image Processing.
[135] Pramod K. Varshney,et al. On performance limits of image segmentation algorithms , 2015, Comput. Vis. Image Underst..