A new image segmentation method based on modified intersecting cortical model

Jian Wei Niu; Si Si Shen; Chao Tong; Xiao Peng Gao; Kong Qiao Wang

A new image segmentation method based on modified intersecting cortical model

Jian Wei Niu^*
, Si Si Shen
, Chao Tong
, Xiao Peng Gao
, Kong Qiao Wang

^*此作品的通讯作者

计算机学院

Beihang University
Nokia China Research Center

科研成果: 期刊稿件 › 文章 › 同行评审

3 引用（Scopus）

摘要

An image segmentation method based on the modified intersecting cortical model (MICM) is proposed to set the MICM parameters adaptively according to the different characteristics of images and choose the optimal segmentation results automatically, which are two main obstacles for the basic intersecting cortical model (ICM) to be used in practice. Experiments show that the comprehensive evaluation value of MICM is close to those of basic pulse coupled neural network (PCNN) and basic intersecting cortical model. Compared with the fuzzy C-means algorithm and OTSU algorithm, MICM is of visually better segmentation and the comprehensive evaluation value of MICM increases by approximately 15% and 13% respectively.

源语言	英语
页（从-至）	56-60
页数	5
期刊	Beijing Youdian Xueyuan Xuebao/Journal of Beijing University of Posts And Telecommunications
卷	33
期	1
出版状态	已出版 - 2月 2010

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title = "A new image segmentation method based on modified intersecting cortical model",

abstract = "An image segmentation method based on the modified intersecting cortical model (MICM) is proposed to set the MICM parameters adaptively according to the different characteristics of images and choose the optimal segmentation results automatically, which are two main obstacles for the basic intersecting cortical model (ICM) to be used in practice. Experiments show that the comprehensive evaluation value of MICM is close to those of basic pulse coupled neural network (PCNN) and basic intersecting cortical model. Compared with the fuzzy C-means algorithm and OTSU algorithm, MICM is of visually better segmentation and the comprehensive evaluation value of MICM increases by approximately 15\% and 13\% respectively.",

keywords = "Image segmentation, Intersecting cortical model, Mutual information, Self-adaptive",

author = "Niu, \{Jian Wei\} and Shen, \{Si Si\} and Chao Tong and Gao, \{Xiao Peng\} and Wang, \{Kong Qiao\}",

year = "2010",

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AU - Niu, Jian Wei

AU - Shen, Si Si

AU - Tong, Chao

AU - Gao, Xiao Peng

AU - Wang, Kong Qiao

PY - 2010/2

Y1 - 2010/2

N2 - An image segmentation method based on the modified intersecting cortical model (MICM) is proposed to set the MICM parameters adaptively according to the different characteristics of images and choose the optimal segmentation results automatically, which are two main obstacles for the basic intersecting cortical model (ICM) to be used in practice. Experiments show that the comprehensive evaluation value of MICM is close to those of basic pulse coupled neural network (PCNN) and basic intersecting cortical model. Compared with the fuzzy C-means algorithm and OTSU algorithm, MICM is of visually better segmentation and the comprehensive evaluation value of MICM increases by approximately 15% and 13% respectively.

AB - An image segmentation method based on the modified intersecting cortical model (MICM) is proposed to set the MICM parameters adaptively according to the different characteristics of images and choose the optimal segmentation results automatically, which are two main obstacles for the basic intersecting cortical model (ICM) to be used in practice. Experiments show that the comprehensive evaluation value of MICM is close to those of basic pulse coupled neural network (PCNN) and basic intersecting cortical model. Compared with the fuzzy C-means algorithm and OTSU algorithm, MICM is of visually better segmentation and the comprehensive evaluation value of MICM increases by approximately 15% and 13% respectively.

KW - Image segmentation

KW - Intersecting cortical model

KW - Mutual information

KW - Self-adaptive

UR - https://www.scopus.com/pages/publications/77951907950

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JO - Beijing Youdian Xueyuan Xuebao/Journal of Beijing University of Posts And Telecommunications

JF - Beijing Youdian Xueyuan Xuebao/Journal of Beijing University of Posts And Telecommunications

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A new image segmentation method based on modified intersecting cortical model

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