基于GS-SVM的彩色图像分割算法
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南京大学电子科学与工程学院 南京 210046

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TN911.73

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Color image segmentation algorithm based on grid search-support vector machine
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College of Electronic Science and Engineering,Nanjing University,Nanjing 210046,China

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    摘要:

    图像分割是图像分析、模式识别等领域的关键技术,为减少光照等因素对颜色的影响,增加图像分割质量,提出一种基于GSSVM的彩色图像分割算法。首先提取图像RGB和HSI颜色分量,组合成样本的特征空间对支持向量机进行训练,训练时利用网格搜索法对支持向量机进行参数寻优,最后训练后的GSSVM对彩色图像进行分割。实验表明该算法能够在网格范围内寻找全局最优解,分割精度达到95.6%,具有良好的精度和鲁棒性,且分割效果更加符合人类视觉特性。

    Abstract:

    Image segmentation is the key technology of image analysis ,pattern recognition and other fields.In order to reduce the impact of factors such as light to color and enhance the quality of image segmentation,a color image segmentation algorithm base on the Grid SearchSupport Vector Machine(GSSVM) is proposed.Firstly, the RGB and HSI components were extracted from image.Then components combined into the feature space of the sample for the training of SVM.The parameters of the SVM were optimized through the grid search method when training.Finally, aftertraining GSSVM segmented the color image.Experience has shown that the algorithm can find the global optimal solution within the space of the grid. The segmentation accuracy of algorithm can be 95.6%.The segmentation algorithm is with good accuracy and robustness. Also,the segmentation result is more in line with the visual characteristics of human.

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黄挺,王元庆,张自豪.基于GS-SVM的彩色图像分割算法[J].电子测量技术,2017,40(7):105-108

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  • 在线发布日期: 2017-08-15
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