.png){kind=icon}
返回
A multistage adaptive thresholding method
.png){kind=icon}
PRE
AI
DOI：10.1016/j.patrec.2004.11.003.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Thresholding is a simple but effective technique for image segmentation. In this paper, a general locally adaptive thresholding method using neighborhood processing is presented. The method makes use of local image statistics of mean and variance within a variable neighborhood and two thresholds obtained from the global intensity distribution. It can thus take advantage of local thresholding and, at the same time, prevent over segmentation with the global image information. We also present a systematic method to calculate a combination coefficient of the mean and the variance based on global image information. Experiments on both optical character recognition (OCR) images and oil sand images demonstrate that this method provides superior image segmentation to existing thresholding methods for images that are severely degraded due to noise, poor illumination and shadow. (c) 2004 Elsevier B.V. All rights reserved.
Keyword:
image segmentation
local thresholding
optical character recognition
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.3
论文数:
7.9K
被引数:
1.6W
机构
暂无机构信息
引用论文
.png){kind=icon}
分享收藏Electrocatalysis at graphite and carbon nanotube modified electrodes: edge-plane sites and tube ends are the reactive sites石墨和碳纳米管修饰电极上的电催化: 边缘平面位和管端是反应位点
PREAI
分享收藏
查看更多内容