An image segmentation approach on improved implicit surface model in straddle strategy

被引:0
|
作者
Zhao, Hailei [1 ]
机构
[1] Jiangnan Univ, Sch Business, Wuxi 214122, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
Implicit surface model; Straddle arbitrage; Image denoising; Image segmentation; Image processing;
D O I
10.1007/s11042-020-08719-7
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
At present, some experts and scholars do not explicitly mention the static model in the analysis of the straddle strategy, which leads to the research results are not ideal. This paper unifies the static model and proposes a method to analyze the arbitrage opportunities in the bond market. At the same time, this paper combines image processing technology to analyze image method and improve image clarity. In addition, this paper uses the contrast method to carry out traditional static model analysis, combines the research requirements to improve the model, obtains the research data through network data collection, and constructs the model for experimental data analysis. Finally, the paper processes the model data through image processing to obtain identifiable statistical images. The research shows that the model proposed in this study has certain validity and can provide theoretical reference for subsequent related research.
引用
收藏
页码:17991 / 18003
页数:13
相关论文
共 50 条
  • [41] Research on image segmentation method based on improved Snake model
    Zhang, Mei
    Meng, Dan
    Pei, Yongtao
    Wen, Jinghua
    MULTIMEDIA TOOLS AND APPLICATIONS, 2024, 83 (05) : 13977 - 13994
  • [42] Image semantic segmentation method based on improved ERFNet model
    Ye, Dexue
    Han, Rubing
    JOURNAL OF ENGINEERING-JOE, 2022, 2022 (02): : 180 - 190
  • [43] Ochotona curzoniae image segmentation based on the improved LBF model
    Zhang A.
    Hu S.
    Chen H.
    Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition), 2016, 44 (02): : 75 - 80
  • [44] Image segmentation for blind lanes based on improved SegNet model
    Xia, Yongquan
    Li, Yiqing
    Ye, Qianqian
    Dong, Jianhua
    JOURNAL OF ELECTRONIC IMAGING, 2023, 32 (01)
  • [45] An improved Snakes model using fuzzy feature for image segmentation
    Shi, Cheng-Xian
    Lin, Hong-Zhong
    Guangdianzi Jiguang/Journal of Optoelectronics Laser, 2010, 21 (03): : 456 - 460
  • [46] Improved Snake model Algorithm with Application in Liver Image Segmentation
    Lan, Hong
    Min, Lequan
    INFORMATION TECHNOLOGY APPLICATIONS IN INDUSTRY, PTS 1-4, 2013, 263-266 : 2643 - 2648
  • [47] Diffusion Models for Implicit Image Segmentation Ensembles
    Wolleb, Julia
    Sandkuhler, Robin
    Bieder, Florentin
    Valmaggia, Philippe
    Cattin, Philippe C.
    INTERNATIONAL CONFERENCE ON MEDICAL IMAGING WITH DEEP LEARNING, VOL 172, 2022, 172 : 1336 - 1348
  • [48] Range image segmentation by surface extraction using an improved robust estimator
    Gotardo, PFU
    Bellon, ORP
    Silva, L
    2003 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOL II, PROCEEDINGS, 2003, : 33 - 38
  • [49] RULE-BASED IMAGE SEGMENTATION - A DYNAMIC CONTROL STRATEGY APPROACH
    LEVINE, MD
    NAZIF, AM
    COMPUTER VISION GRAPHICS AND IMAGE PROCESSING, 1985, 32 (01): : 104 - 126
  • [50] An improved image segmentation approach based on level set and mathematical morphology
    Li, H
    Elmoataz, A
    Fadili, J
    Ruan, S
    THIRD INTERNATIONAL SYMPOSIUM ON MULTISPECTRAL IMAGE PROCESSING AND PATTERN RECOGNITION, PTS 1 AND 2, 2003, 5286 : 851 - 854