Laser & Optoelectronics Progress, Volume. 61, Issue 8, 0837005(2024)

A Robust Image Segmentation Algorithm Based on Weighted Filtering and Kernel Metric

Yi Liu1, Xiaofeng Zhang1,2、*, Yujuan Sun1, Hua Wang1, and Caiming Zhang3
Author Affiliations
  • 1School of Information and Electrical Engineering, Ludong University, Yantai 264025, Shandong , China
  • 2School of Information Engineering, Yantai Institute of Technology, Yantai 264003, Shandong , China
  • 3School of Software, Shandong University, Jinan 250014, Shandong , China
  • show less
    References(40)

    [1] Wang C, Wang Y S, Di F. Fast automatic fuzzy C- means clustering color image segmentation algorithm[J]. Laser & Optoelectronics Progress, 59, 2210001(2022).

    [2] Yao T, Wang G, Yan L S et al. Online latent semantic hashing for cross-media retrieval[J]. Pattern Recognition, 89, 1-11(2019).

    [3] Liao K Y, Huang G, Zheng Y L et al. Approximate object location deep visual representations for image retrieval[J]. Displays, 77, 102376(2023).

    [4] Huang B J, Wang Z Y, Wang G C et al. PLFace: progressive learning for face recognition with mask bias[J]. Pattern Recognition, 135, 109142(2023).

    [5] Yin H P, Chen B, Chai Y et al. Vision-based object detection and tracking: a review[J]. Acta Automatica Sinica, 42, 1466-1489(2016).

    [6] Cai Y L, Mi S H, Yan J H et al. An unsupervised segmentation method based on dynamic threshold neural P systems for color images[J]. Information Sciences, 587, 473-484(2022).

    [7] Zhu Z Q, He X Y, Qi G Q et al. Brain tumor segmentation based on the fusion of deep semantics and edge information in multimodal MRI[J]. Information Fusion, 91, 376-387(2023).

    [8] Zhang X F, Wang H, Zhang Y et al. Improved fuzzy clustering for image segmentation based on a low-rank prior[J]. Computational Visual Media, 7, 513-528(2021).

    [9] Liu H, Xu J, Wu Y et al. Learning deconvolutional deep neural network for high resolution medical image reconstruction[J]. Information Sciences, 468, 142-154(2018).

    [10] Liu H, Wang H O, Wu Y et al. Superpixel region merging based on deep network for medical image segmentation[J]. ACM Transactions on Intelligent Systems and Technology, 11, 39.

    [11] Fu X W, Shan H L, Lü Z K et al. Synthetic aperture radar image denoising algorithm based on deep learning[J]. Acta Optica Sinica, 43, 0610002(2023).

    [12] Aljabri M, AlGhamdi M. A review on the use of deep learning for medical images segmentation[J]. Neurocomputing, 506, 311-335(2022).

    [13] Bezdek J C, Ehrlich R, Full W. FCM: the fuzzy c-means clustering algorithm[J]. Computers & Geosciences, 10, 191-203(1984).

    [14] Guo Q, Peng L. Hyperspectral classification based on 3D convolutional neural network and super pixel segmentation[J]. Acta Optica Sinica, 41, 2210001(2021).

    [15] Yu X, Liu H, Lin Y X et al. Auto-weighted sample-level fusion with anchors for incomplete multi-view clustering[J]. Pattern Recognition, 130, 108772(2022).

    [16] Ahmed M N, Yamany S M, Mohamed N et al. A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data[J]. IEEE Transactions on Medical Imaging, 21, 193-199(2002).

    [17] Krinidis S, Chatzis V. A robust fuzzy local information C-means clustering algorithm[J]. IEEE Transactions on Image Processing, 19, 1328-1337(2010).

    [18] Cai W L, Chen S C, Zhang D Q. Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation[J]. Pattern Recognition, 40, 825-838(2007).

    [19] Szilagyi L, Benyo Z, Szilagyi S M et al. MR brain image segmentation using an enhanced fuzzy C-means algorithm[C], 724-726(2004).

    [20] Gharieb R R, Gendy G. Fuzzy C-means with a local membership KL distance for medical image segmentation[C], 47-50(2015).

    [21] Gong M G, Liang Y, Shi J et al. Fuzzy C-means clustering with local information and kernel metric for image segmentation[J]. IEEE Transactions on Image Processing, 22, 573-584(2013).

    [22] Lei T, Jia X H, Zhang Y N et al. Significantly fast and robust fuzzy C-means clustering algorithm based on morphological reconstruction and membership filtering[J]. IEEE Transactions on Fuzzy Systems, 26, 3027-3041(2018).

    [23] Wang Q S, Wang X P, Fang C et al. Robust fuzzy c-means clustering algorithm with adaptive spatial & intensity constraint and membership linking for noise image segmentation[J]. Applied Soft Computing, 92, 106318(2020).

    [24] Wang Z J, Yu Z J, Ma K et al. An image filtering algorithm based on adaptive median and gradient inverse weight[J]. Laser & Optoelectronics Progress, 54, 121001(2017).

    [25] Niu M J, Zhang Y J, Li Z et al. Remote sensing image segmentation network based on adaptive multiscale and contour gradient[J]. Laser & Optoelectronics Progress, 60, 0228009(2023).

    [26] Cheng M M, Mitra N J, Huang X L et al. Global contrast based salient region detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37, 569-582(2014).

    [27] Shi P F, Guo L, Cui H R et al. Geometric consistent fuzzy cluster ensemble with membership reconstruction for image segmentation[J]. Digital Signal Processing, 134, 103901(2023).

    [28] Wu C M, Yang X Q. Robust credibilistic fuzzy local information clustering with spatial information constraints[J]. Digital Signal Processing, 97, 102615(2020).

    [29] Simões E C, de Carvalho F A T. Gaussian kernel fuzzy c-means with width parameter computation and regularization[J]. Pattern Recognition, 143, 109749(2023).

    [30] Saha A, Das S. Stronger convergence results for the center-based fuzzy clustering with convex divergence measure[J]. IEEE Transactions on Cybernetics, 49, 4229-4242(2019).

    [31] Hiriart-Urruty J B, Strodiot J J, Nguyen V H. Generalized Hessian matrix and second-order optimality conditions for problems with C1, 1 data[J]. Applied Mathematics and Optimization, 11, 43-56(1984).

    [32] Chen S C, Zhang D Q. Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 34, 1907-1916(2004).

    [33] Martin D, Fowlkes C, Tal D et al. A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics[C], 416-423(2002).

    [34] Xia G S, Hu J W, Hu F et al. AID: a benchmark data set for performance evaluation of aerial scene classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 55, 3965-3981(2017).

    [35] Ronneberger O, Fischer P, Brox T, Navab N, Hornegger J, Wells W M et al. U-net: convolutional networks for biomedical image segmentation[M]. Medical image computing and computer-assisted intervention-MICCAI 2015. Lecture notes in computer science, 9351, 234-241(2015).

    [36] Chen L C, Zhu Y K, Papandreou G, Ferrari V, Hebert M, Sminchisescu C et al. Encoder-decoder with atrous separable convolution for semantic image segmentation[M]. Computer vision-ECCV 2018. Lecture notes in computer science, 11211, 833-851(2018).

    [37] Tschandl P, Rosendahl C, Kittler H. The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions[J]. Scientific Data, 5, 180161(2018).

    [40] Zhou J F, Li J H, Gao W Q et al. Combination of continuous wavelet transform and genetic algorithm-based Otsu for efficient mass spectrometry peak detection[J]. Biochemical and Biophysical Research Communications, 624, 75-80(2022).

    Tools

    Get Citation

    Copy Citation Text

    Yi Liu, Xiaofeng Zhang, Yujuan Sun, Hua Wang, Caiming Zhang. A Robust Image Segmentation Algorithm Based on Weighted Filtering and Kernel Metric[J]. Laser & Optoelectronics Progress, 2024, 61(8): 0837005

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Digital Image Processing

    Received: Jun. 15, 2023

    Accepted: Jul. 24, 2023

    Published Online: Apr. 2, 2024

    The Author Email: Zhang Xiaofeng (iamzxf@126.com)

    DOI:10.3788/LOP231545

    Topics