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基于改进的自适应差分演化算法的二维Otsu多阈值图像分割

罗钧 杨永松 侍宝玉

引用本文: 罗钧, 杨永松, 侍宝玉. 基于改进的自适应差分演化算法的二维Otsu多阈值图像分割[J]. 电子与信息学报, 2019, 41(8): 2017-2024. doi: 10.11999/JEIT180949 shu
Citation:  Jun LUO, Yongsong YANG, Baoyu SHI. Multi-threshold Image Segmentation of 2D Otsu Based on Improved Adaptive Differential Evolution Algorithm[J]. Journal of Electronics and Information Technology, 2019, 41(8): 2017-2024. doi: 10.11999/JEIT180949 shu

基于改进的自适应差分演化算法的二维Otsu多阈值图像分割

    作者简介: 罗钧: 男,1963年生,教授,博士生导师,研究方向为模式识别与人工智能,精密机械及测试计量,智能信息处理;
    杨永松: 男,1994年生,硕士生,研究方向为嵌入式系统,机器视觉;
    侍宝玉: 女,1994年生,硕士生,研究方向为嵌入式系统,机器视觉
    通讯作者: 罗钧,luojun@cqu.edu.cn
摘要: 针对常规最大类间方差法在多阈值图像分割中存在的运算量大、计算时间长、分割精度较低等问题,该文提出一种基于改进的自适应差分演化(JADE)算法的2维Otsu多阈值分割法。首先,为增强初始化种群的质量、提升控制参数的适应性,将混沌映射机制融入到JADE算法中;进而,通过该改进算法求解2维 Otsu 多阈值图像的最佳分割阈值;最终,将该算法与差分进化(DE), JADE,改进正弦参数自适应的差分进化(LSHADE-cnEpSin)以及增强的适应性微分变换差分进化(EFADE) 4种算法的2维Otsu多阈值图像分割进行比较。实验结果表明,与其它4种算法相比,基于改进JADE算法的2维Otsu多阈值图像分割在分割速度以及精度上均有较明显的改善。

English

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  • 图 1  2维多阈值分割直方图

    图 2  基于CJADE算法2维Otsu多阈值分割方法流程图

    图 3  分割效果图

    图 4  进化曲线图

    表 1  算法1:混沌映射更新参数uFuCR的伪代码

     (1) If $\;\alpha < \beta $
     (2)   ${u_{\rm CR}} = {u_1} \cdot {u_{\rm CR}} \cdot (1 - {u_{\rm CR}})$
     (3)   ${u_F} = {u_2} \cdot {u_F} \cdot (1 - {u_F})$
     (4) Else
     (5)   ${u_{\rm CR}} = (1 - c) \cdot {u_{\rm CR}} + c \cdot {{\rm mean}_{\rm A}}({S_{\rm CR}})$
     (6)   ${u_F} = (1 - c) \cdot {u_F} + c \cdot {{\rm mean}_{\rm L}}({S_F})$
     (7) End If
    下载: 导出CSV

    表 2  PSNR、运算时间以及迭代次数的对比

    算法Lena (512$ \times $512)Finger (256$ \times $256)Pepper (512$ \times $512)
    2阈值3阈值4阈值2阈值3阈值4阈值2阈值3阈值4阈值
    DE算法PSNR(dB)10.5813.8815.6412.0212.4514.1411.6815.8416.54
    收敛时间(s)7.797.827.843.643.583.738.498.348.82
    迭代次数725864625766454347
    JADE算法PSNR(dB)11.7914.2516.0212.3513.0214.2611.7116.3216.71
    收敛时间(s)0.850.830.770.510.530.570.810.800.83
    迭代次数525450596258605658
    LSHADE-cnEpSin算法PSNR(dB)13.7014.9815.6712.0712.7714.4612.2316.1917.02
    收敛时间(s)0.790.750.820.450.480.460.780.820.78
    迭代次数343533654560504846
    EFADE算法PSNR(dB)12.8915.0515.4513.2312.6113.2412.1115.5716.67
    收敛时间(s)0.991.121.100.770.760.831.241.311.29
    迭代次数454246504852403841
    CJADE算法PSNR(dB)13.9315.6416.2513.6514.6714.8912.5616.5717.12
    收敛时间(s)0.640.660.650.450.440.480.610.640.66
    迭代次数383538414044403638
    下载: 导出CSV

    表 3  阈值和距离测度值的对比

    算法Lena (512$ \times $512)Finger (256$ \times $256)Pepper (512$ \times $512)
    2阈值3阈值4阈值2阈值3阈值4阈值2阈值3阈值4阈值
    DE算法距离测度4645.674698.864747.741223.451247.751296.255340.875407.715513.28
    阈值(68,71)
    (117,153)
    (30, 32)
    (86,138)
    (193,199)
    (88,95)
    (119,123)
    (151,153)
    (202,207)
    (39,53)
    (155,165)
    (108,124)
    (147,152)
    (168,180)
    (23,38)
    (102,133)
    (150,157)
    (169,170)
    (70,70)
    (117,161)
    (84, 85)
    (142,162)
    (201,203)
    (70,77)
    (111,112)
    (126,129)
    (129,179)
    JADE算法距离测度4842.774912.214924.131315.431320.351326.235798.465822.865892.86
    阈值(89,149)
    (193,195)
    (77,79)
    (114,149)
    (196,196)
    (70,77)
    (109,137)
    (149,154)
    (182,183)
    (138,166)
    (175,175)
    (10,67)
    (143,164)
    (174,175)
    (40,52)
    (50,110)
    (156,156)
    (171,172)
    (88,91)
    (127,169)
    (98, 115)
    (140,140)
    (178,178)
    (96,101)
    (114,133)
    (149,150)
    (152,171)
    LSHADE-cnEpSin算法距离测度4862.494905.974995.041256.651268.791289.325797.855899.345909.58
    阈值(88,149)
    (194,195)
    (79,79)
    (115,145)
    (177,177)
    (76,76)
    (119,141)
    (158,160)
    (197,197)
    (88,102)
    (183,183)
    (64,82)
    (148,164)
    (183,184)
    (36,39)
    (42,98)
    (145,155)
    (164,169)
    (78,79)
    (126,177)
    (84, 85)
    (127,159)
    (194,194)
    (76,77)
    (121,122)
    (126,157)
    (192,193)
    EFADE算法距离测度4848.874951.824973.231257.291267.421324.415788.615885.725892.13
    阈值(89,148)
    (186,186)
    (76,80)
    (130,153)
    (205,205)
    (79,86)
    (112,137)
    (139,151)
    (201,203)
    (44,51)
    (142,176)
    (30,42)
    (140,162)
    (172,174)
    (41,46)
    (68,83)
    (141,167)
    (172,173)
    (86,90)
    (120,176)
    (73, 74)
    (121,159)
    (193,194)
    (53,55)
    (121,123)
    (154,154)
    (180,182)
    CJADE算法距离测度4863.534977.344999.631327.841329.171331.285799.135898.735912.18
    阈值(87,149)
    (194,194)
    (77,78)
    (115,148)
    (194,195)
    (78,80)
    (117,139)
    (156,156)
    (199,199)
    (143,166)
    (173,173)
    (25, 62)
    (142,166)
    (174,175)
    (40,45)
    (70,98)
    (156,158)
    (162,162)
    (84,85)
    (124,173)
    (77, 78)
    (123,164)
    (195,195)
    (54,55)
    (99,100)
    (129,160)
    (199,199)
    下载: 导出CSV
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文章相关
  • 通讯作者:  罗钧, luojun@cqu.edu.cn
  • 收稿日期:  2018-10-12
  • 录用日期:  2019-03-04
  • 网络出版日期:  2019-03-28
  • 刊出日期:  2019-08-01
通讯作者: 陈斌, bchen63@163.com
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