| 基于图像复杂度曲线拟合的快速图像分割方法 |
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| 引用本文： | 王海峰,章怡,蒋益锋.基于图像复杂度曲线拟合的快速图像分割方法[J].计算机科学,2018,45(2):130-134. |
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| 作者姓名： | 王海峰 章怡 蒋益锋 |
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| 作者单位： | 江苏理工学院信息中心 江苏 常州213001,江苏理工学院信息中心 江苏 常州213001,江苏理工学院信息中心 江苏 常州213001 |
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| 基金项目： | 本文受江苏省自然科学基金项目(BY2016030-08),江苏省常州市科技计划资助 |
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| 摘 要： | 针对经典Otsu算法、最大熵算法、最小交叉熵算法等在 低 信噪比图像中分割效果较差的问题,从图像复杂度的角度提出了基于图像背景与目标的对象复杂度的图像分割方法,并采用曲线拟合方法大大减少了计算冗余,提高了算法的实时性与稳定性。实验表明,与经典算法相比,所提快速分割算法具有运行速度快、稳定性与可靠性高等特点,能够有效地解决 低信噪比图像分割效果较差的问题。
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| 关 键 词： | 图像复杂度 最大熵算法 最小交叉熵 曲线拟合 图像分割 |
| 收稿时间： | 2017/4/1 0:00:00 |
| 修稿时间： | 2017/5/22 0:00:00 |
Fast Image Segmentation Method Based on Image Complexity through Curve Fitting |
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| WANG Hai-feng,ZHANG Yi and JIANG Yi-feng.Fast Image Segmentation Method Based on Image Complexity through Curve Fitting[J].Computer Science,2018,45(2):130-134. |
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| Authors: | WANG Hai-feng ZHANG Yi and JIANG Yi-feng |
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| Affiliation: | Information Center,Jiangsu University of Technology,Changzhou,Jiangsu 213001,China,Information Center,Jiangsu University of Technology,Changzhou,Jiangsu 213001,China and Information Center,Jiangsu University of Technology,Changzhou,Jiangsu 213001,China |
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| Abstract: | The classical Otsu algorithm,maximum entropy algorithm,and minimum cross entropy algorithm have poor segmentation image effect when image signal noise ratio (SNR) is low.The paper proposed a kind of image segmentation method based on image background and target object complexity from the perspective of the image complexity,greatly reducing redundancy with the curve fitting method and improving the real-time performance and stability of the algorithm.According to the experiment results,compared with the classical algorithm,the fast segmentation algorithm proposed in the paper has high operation speed,stability and reliability,and can effectively solve dissatisfactory image segmentation effect when image SNR is low. |
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| Keywords: | Image complexity Maximum entropy algorithm Minimum cross entropy Curve fitting Image segmentation |
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