计算机工程与应用 ›› 2013, Vol. 49 ›› Issue (16): 155-157.

• 图形图像处理 • 上一篇    下一篇

基于复杂性指数的图像分割必要性判别技术

魏  庆1,卢照敢1,2,邵  超1   

  1. 1.河南财经政法大学 计算机与信息工程学院,郑州 450002
    2.西安交通大学 电子与信息工程学院,西安 710049
  • 出版日期:2013-08-15 发布日期:2013-08-15

Discriminatory technology of necessity for image segmentation based on complexity index

WEI Qing1, LU Zhaogan1,2, SHAO Chao1   

  1. 1.School of Computer and Information Engineering, Henan University of Economics and Law, Zhengzhou 450002, China
    2.School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China
  • Online:2013-08-15 Published:2013-08-15

摘要: 考虑到图像分割的复杂性实质上与图像中可分割的区域个数相关,而图像分割的必要性是与图像中可分割的区域大小有关,针对图像分割实际应用中部分图像的内容较少、无明显语义,不必进行图像分割的情况,提出一种基于图像内容语义、图像分割复杂性的图像分割必要性判别测度。进一步基于其测度定义,进行了大量相关实验,实验结果表明,基于复杂性指数的图像分割测度很好地完成了预期的功能,能够成为图像分割必要性有效合理的衡量依据。

关键词: 图像分割, 复杂性, 测度

Abstract: Considering the complexity of image segmentation is essentially associated with the number of divisible area of image, and the necessity for image segmentation is related to the size of the dividable region in the image, in view of some of the image contents are less and lack of clear semantics, even unnecessary for segmentation in the practical application of image segmentation, an image segmentation necessity discriminatory measures based on image content semantics and the complexity of image segmentation is proposed. A lot of experiments based on the measure definition are carried out. Experimental results show that the proposed image segmentation based on complexity index measure well implements the expected function. The image segmentation based on complexity index measure can be the effective and reasonable measure for the image segmentation necessity.

Key words: image division, complexity, evaluation index