计算机科学 ›› 2011, Vol. 38 ›› Issue (12): 278-280.

• 图形图像 • 上一篇    下一篇

基于改进的Sobel算子最大嫡图像分割研究

章慧,龚声蓉   

  1. (淮阴工学院计算机工程学院 淮安223003);(苏州大学计算机科学与技术学院 苏州215006)
  • 出版日期:2018-12-01 发布日期:2018-12-01

Image Segmentation Based on Sobel Operator and Maximum Entropy Algorithm

  • Online:2018-12-01 Published:2018-12-01

摘要: 研究图像分割精度问题。针对传统的Sobel算子图像分割容易造成图像分割不清晰、对比度不明显、分割精度低等问题缺陷,提出一种改进的Sobel算子的二维最大墒数字图像分割方法。算法首先根据数字图像特征对图像进行初分割,然后应用Sobel算子检测出数字图像真正的边缘,将通过Sobel算法边缘检测获得的阂值应用到二维最大墒分割方法中。对数字图像目标和目标边缘分别使用不同的阂值进行分割,解决由于局部图像叠加而产生的分割不准确的问题。仿真实验表明,提出的算法对图像分割鲁棒性好,分割准确率高,是一种有效适用的算法。

关键词: Sobel算子,最大嫡算法,图像分割,边缘检测

Abstract: Image segmentation accuracy problem was researched. In traditional Sobel operator, image segmentation easi1y causes the image segmentation not clear, and contrast is not apparent, segmentation accuracy is low, so, the article put forward an improved Sobcl operator 2-d maximum entropy digital image segmentation method. Algorithm firstly makes image segmentation according to digital image characteristics, then Sobel operator is used to detect real digital image edge, and Sobel edge detection algorithm obtains the threshold value which is used to the 2-d maximum entropy image segmentation method. Based on digital image goals and objectives fringe parting, this paper used different threshold segmentation to solve the segmentation inaccurate problem produced by local image stack. Simulation experiments show that the proposed algorithm for image segmentation has good robustness,segmentation rate,which is an effective applicable algorithm.

Key words: Sobel operator, Maximum entropy algorithm, Image segmentation, Edge detection

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