Image contour detection based on improved level set in complex environment

Li, Dan; Bei, Lulu; Bao, Jin-An; Yuan, Sizhen; Huang, Kai

doi:10.1007/s11276-021-02664-5

Cited by 9 publications

(2 citation statements)

References 35 publications

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“…rough image feature analysis and edge feature detection technology [5], the main features of sports training sports images are extracted. Edge contour detection [6] and corner detection technology realize motion capture in sports training [7], aiming at actual training in various sports [8]. Research on the application of capture methods in sports training has received widespread attention.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Sports Action Recognition Based on Image Processing Technology and Analysis of the Development of Sports Industry Pattern

Zhao-yin

Zhang

Sun

2021

Scientific Programming

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The current era is an information age, and society is turning to the information age. The image processing technology is also widely used in various fields, and the technology of sports action recognition based on image processing technology can also be said to be appropriate. This article uses a spatial visual feature analysis algorithm to implement it. To implement this algorithm, a series of work such as image collection, feature extraction, and action recognition must be completed first and then implemented through texture functions and other related functions. This algorithm can be used to complete the image-based sports action recognition technology at the minimum time cost. This algorithm can help sportsmen better complete training and standardize movements to a certain extent. As for the development of China’s current sports industry structure, it is also steadily improving. The people’s love for sports is getting stronger and stronger, which also makes the development of China’s sports industry still benefit a lot.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Sports Action Recognition Based on Image Processing Technology and Analysis of the Development of Sports Industry Pattern

Zhao-yin

Zhang

Sun

2021

Scientific Programming

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“…For the last few years, level-set-based models (LSBMs) [1][2][3][4] played a key role in the tasks of image segmentation due to their advantages, namely convenient modeling, easy programming, and efficient computation. Currently, LSBMs can essentially be divided into three categories: local characteristic-based LSBMs (LCLSBMs) [5][6][7][8], global characteristic-based LSBMs (GCLSBMs) [9][10][11][12], and hybrid characteristic-based LSBMs (HCLSBMs) [13][14][15][16]. GCLSBMs usually draw on global characteristics of images, such as the global inter-class variance (ICV) [17], global coefficient of variation [18], global area descriptor [19], global area-based pressure force [20], and so on, to guide the level sets; they are successful in segmenting images with homogeneous pixels.…”

Section: Introductionmentioning

confidence: 99%

Level Sets Guided by SoDEF-Fitting Energy for River Channel Detection in SAR Images

Han

Basu

2023

Remote Sensing

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To achieve river channel detection in SAR (synthetic aperture radar) images, we developed a level-set-based model (LSBM) guided by a designed data-fitting energy which is called the SoDEF (sum of dual exponential functions)-fitting energy. Firstly, we designed a function by computing the sum of dual exponential functions to substitute for the quadratic function, and used it to construct the data-fitting energy. Secondly, the adaptive area-fitting centers (AFCs) were computed based on two kinds of grayscale characteristics, which are more accurate and more stable. Thirdly, the Dirac function in gradient descent flow was displaced by an edge indicator function to help the evolving level sets stop at the target edges. Moreover, some regularized terms were incorporated into the objective function to guarantee the model’s stability. The river channel detection experiments conducted with real SAR images indicated that the developed model is superior to the related state-of-the-art methods in its detection accuracy and efficiency.

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Welcome to Heshan: An Installation to Create Immersive and Entertaining Experiences with Local Art Through Interactive Media Technologies

Zhou

Xie

2022

Lecture Notes in Computer Science

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Image contour detection based on improved level set in complex environment

Cited by 9 publications

References 35 publications

[Retracted] Sports Action Recognition Based on Image Processing Technology and Analysis of the Development of Sports Industry Pattern

[Retracted] Sports Action Recognition Based on Image Processing Technology and Analysis of the Development of Sports Industry Pattern

Level Sets Guided by SoDEF-Fitting Energy for River Channel Detection in SAR Images

Welcome to Heshan: An Installation to Create Immersive and Entertaining Experiences with Local Art Through Interactive Media Technologies

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