Analysis and Design of Image Segmentation Algorithm Based on Super-pixel and Graph Cut

[1]Greig D, Porteous B, Seheult A. Exact maximum a posteriori estimation for binary images[J].J.Royal Statistical Soc., Series B, 1989,51(2):271-2279GreigDPorteousBSeheultA.Exact maximum a posteriori estimation for binary images[J]J.Royal Statistical Soc., Series B198951(2):271227910.1111/j.2517-6161.1989.tb01764.xSearch in Google Scholar

[2]Boykov Y Y, Jolly M. Interactive graph cut for optimal boundary & region segmentation of objects in N-D images[C], Proceedings of Internation Conference on Computer Vision. Vancouver, Cannada: IEEE Computer Society, 2001, I: 105-112BoykovY YJollyM.Interactive graph cut for optimal boundary & region segmentation of objects in N-D images[C]Proceedings of Internation Conference on Computer VisionVancouver, CannadaIEEE Computer Society2001I105112Search in Google Scholar

[3]Boykov Y, Kolmogorov V. An experimental comparison of min-cut/max flow algorithms for energy minimization in vision[J]. IEEE Transactions on Pattern Analysis and Machine Intelligen-ce, 2004, 26(9): 1124-1137BoykovYKolmogorovV.An experimental comparison of min-cut/max flow algorithms for energy minimization in vision[J]IEEE Transactions on Pattern Analysis and Machine Intelligen-ce200426(9):1124113710.1007/3-540-44745-8_24Search in Google Scholar

[4]ROTHER C. KOLMOGOROV V. BLAKE A. GrabCut: interactive foregroud extraction using iterated graph cuts [J]. ACM Transactions on Graphics (TOC), 2004,23(3),309-314.ROTHERC.KOLMOGOROVV.BLAKEA.GrabCut: interactive foregroud extraction using iterated graph cuts [J]ACM Transactions on Graphics (TOC),200423(3)30931410.1145/1186562.1015720Search in Google Scholar

[5]Qiang Nan. Image Segmentation Algorithm Based on Morphological Watershed and Spectral Clustering [D]. Chang'an University, 2014.NanQiangImage Segmentation Algorithm Based on Morphological Watershed and Spectral Clustering [D]Chang'an University,2014Search in Google Scholar

[6]Zhang Jiashu, Li Beichuan. Research on Two-Dimensional Maximum Entropy Threshold Segmentation of Gray Image[J].Journal of Southwest China Normal University(Natural Science), 1995,(06):643-647.JiashuZhangBeichuanLiResearch on Two-Dimensional Maximum Entropy Threshold Segmentation of Gray Image[J]Journal of Southwest China Normal University(Natural Science)1995(06):643647Search in Google Scholar

[7]Xi Jing. Remote Sensing Image Edge Detection and Its Application in Channel GIS [D]. Southeast University, 2006.JingXiRemote Sensing Image Edge Detection and Its Application in Channel GIS [D]Southeast University2006Search in Google Scholar

[8]Wu Jian. Research and application of motion human detection and tracking in video sequences [D]. Lanzhou Institute of Technology, 2010.JianWuResearch and application of motion human detection and tracking in video sequences [D]Lanzhou Institute of Technology2010Search in Google Scholar

[9]Meng Jie, Cheng Yongqiang. Application of Image Location and Segmentation in Vehicle License Plate Recognition[J]. Information Communication, 2015,(09):159-160.JieMengYongqiangChengApplication of Image Location and Segmentation in Vehicle License Plate Recognition[J]Information Communication2015(09):159160Search in Google Scholar

[10]Tang Xiaojing. Color vector error diffusion algorithm based on edge detection[J]. Science and Technology Information, 2009, (35):482-483XiaojingTangColor vector error diffusion algorithm based on edge detection[J]Science and Technology Information,2009(35):482483Search in Google Scholar

[11]Guo Zhenfeng. Interactive Image Segmentation Based on Graph Cuts [D]. Central South University, 2013.ZhenfengGuoInteractive Image Segmentation Based on Graph Cuts [D]Central South University2013Search in Google Scholar

[12]Cao Jiannong, FANG Danxia. Image Segmentation Method Based on Graph Theory and Its Limitations[J]. Surveying and Mapping Techniques, 2006, (02)JiannongCaoDanxiaFANGImage Segmentation Method Based on Graph Theory and Its Limitations[J]Surveying and Mapping Techniques2006(02)Search in Google Scholar

[13]Wang Chunyao, CHEN Junzhou, LI Wei. Review of research on superpixel segmentation algorithm[J]. Journal of Computer Applications, 2014, (01): 6-12.ChunyaoWangJunzhouCHENWeiLIReview of research on superpixel segmentation algorithm[J]Journal of Computer Applications2014(01):612Search in Google Scholar

[14]Yin Li,JianSun,Chi-keung Tang and Heung-Yeung Shum. Lazy Snapping.ICCV 2004LiYinSunJianTangChi-keungShumHeung-YeungLazy SnappingICCV200410.1145/1186562.1015719Search in Google Scholar

[15]Li Xuchao, Zhu Shanan. A Survey of Markov Random Field Methods in Image Segmentation[J]. Journal of Image and Graphics, 2007, (05): 789-798.XuchaoLiShananZhuA Survey of Markov Random Field Methods in Image Segmentation[J]Journal of Image and Graphics2007(05):789798Search in Google Scholar

[16]Xu Huanhuan. Research on image segmentation method based on energy function[D]. University of Science and Technology of China, 2009.HuanhuanXuResearch on image segmentation method based on energy function[D]University of Science and Technology of China2009Search in Google Scholar

[17]Xu Qiuping. Research on target extraction method based on graph cut theory [D]. Shaanxi Normal University, 2009.QiupingXuResearch on target extraction method based on graph cut theory [D]Shaanxi Normal University2009Search in Google Scholar

[18]Wang Yarong. Research on interactive image segmentation based on graph cut[D]. Northwest University, 2011.YarongWangResearch on interactive image segmentation based on graph cut[D]Northwest University2011Search in Google Scholar

[19]Automatic Segmentation of Magnetic Resonance Brain Image Based on Watershed Algorithm[J]. SONG Liwei, SONG Chaoyu, ZHUANG Tiange. Journal of Shanghai Jiaotong University. 2003(11)Automatic Segmentation of Magnetic Resonance Brain Image Based on Watershed Algorithm[J]LiweiSONGChaoyuSONGTiangeZHUANGJournal of Shanghai Jiaotong University2003(11)Search in Google Scholar

[20]Song Yutan, JI Xiu. Research on Binary Image Segmentation Algorithm Based on Mathematical Morphology[J]. Journal of Changchun Institute of Technology (Natural Science Edition), 2008, (3): 68-70.YutanSongXiuJIResearch on Binary Image Segmentation Algorithm Based on Mathematical Morphology[J]Journal of Changchun Institute of Technology (Natural Science Edition)2008(3):6870Search in Google Scholar

[21]Xu Huanhuan. Research on image segmentation method based on energy function[D]. University of Science and Technology of China, 2009.HuanhuanXuResearch on image segmentation method based on energy function[D]University of Science and Technology of China2009Search in Google Scholar

[22]Shi Dianguo. Gray Image Segmentation Based on Graph Theory[D]. Wuhan University of Technology, 2009.DianguoShiGray Image Segmentation Based on Graph Theory[D]Wuhan University of Technology2009Search in Google Scholar

[23]LI Minguang,DENG Kazhong,ZHAO Yin. Remote Sensing Image Segmentation Based on Improved Watershed Transform[J]. Remote Sensing Information, 2009,(06):3-6.MinguangLIKazhongDENGYinZHAORemote Sensing Image Segmentation Based on Improved Watershed Transform[J]Remote Sensing Information2009(06):3610.1117/12.833691Search in Google Scholar

[24]Liu Chen. Application of Filtering Preprocessing in Watershed Segmentation Algorithm[J]. Journal of Kashgar Teachers, 2014, (06): 45-49ChenLiuApplication of Filtering Preprocessing in Watershed Segmentation Algorithm[J]Journal of Kashgar Teachers2014(06):4549Search in Google Scholar

[25]Zhang Xiaolong. Small class division of forest resources survey based on high spatial resolution remote sensing image[D]. Xi'an University of Science and Technology, 2010.XiaolongZhangSmall class division of forest resources survey based on high spatial resolution remote sensing image[D]Xi'an University of Science and Technology201010.1117/12.864998Search in Google Scholar

[26]Liu Huan, Zhang Mei, Peng Xingxing. Research on color image segmentation based on edge detection and region growing[J]. China New Communication, 2016, (11):153-154.HuanLiuMeiZhangXingxingPengResearch on color image segmentation based on edge detection and region growing[J]China New Communication2016(11):153154Search in Google Scholar

[27]Wang Kang. Improvement of k-means clustering algorithm and its application [D]. Dalian University of Technology, 2014.KangWangImprovement of k-means clustering algorithm and its application [D]Dalian University of Technology2014Search in Google Scholar