A survey on Otsu image segmentation methods

被引：0

作者：

机构：

[1] College of Computer Science, Sichuan University

[2] College of Information Science and Technology, Chengdu University

[3] College of Information Science and Technology, Chengdu University of Technology

[4] Faculty of Computer Science, Chengdu Normal University

[5] Chengdu Aeronautic Vocational and Technical College

来源：

Li, S. (lism@cdut.edu.cn) | 1600年 / Binary Information Press卷 / 10期

关键词：

Image segmentation; Natural computation; Otsu method;

D O I：

10.12733/jcis10307

中图分类号：

学科分类号：

摘要：

Image segmentation, involving the processing of concrete image data and the abstract knowledge expression, has been a classic difficult problem and research hotspot in the field of image processing. Otsu is a non-parametric unsupervised method to select global threshold. The one-dimensional Otsu method proposed by Nobuyuki Otsu is based on the one-dimensional histogram, and threshold selection refers to only the pixel gray value, with no spatial information between pixels considered, thus it cannot effectively deal with the noisy image. Later, two-dimensional and three-dimensional Otsu methods with better performance and applicability into noisy images have been proposed by other scholars, but the increase of histogram dimension also leads to the higher computational complexity. However, it is feasible to adopt natural computation algorithm to optimize the computation process. 1553-9105/Copyright © 2014 Binary Information Press.

引用

页码：4287 / 4298

页数：11

共 27 条

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