Extracting Attention Information Algorithm Based onContrast Sensitivity and Markov Chain
电子学报2010年38卷第2A期 页码:213-217
作者机构:
1. 1'吉林大学计算机科学与技术学院,吉林,长春,130012
2. '吉林大学符号计算与知识工程教育部重点实验室,吉林,长春,130012
3. '长春师范学院计算机科学与技术学院,吉林,长春,130032
作者简介:
基金信息:
DOI:
中图分类号:TP391
纸质出版:2010
稿件说明:
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FONT face, Verdana, 张孝临, 等. 基于对比敏感度和马尔可夫链的注意信息提取算法[J]. 电子学报, 2010,38(2A):213-217.
FONT face, Verdana, ZHANG Xiao-lin, et al. Extracting Attention Information Algorithm Based onContrast Sensitivity and Markov Chain[J]. Acta Electronica Sinica, 2010, 38(2A): 213-217.
FONT face, Verdana, 张孝临, 等. 基于对比敏感度和马尔可夫链的注意信息提取算法[J]. 电子学报, 2010,38(2A):213-217.DOI:
FONT face, Verdana, ZHANG Xiao-lin, et al. Extracting Attention Information Algorithm Based onContrast Sensitivity and Markov Chain[J]. Acta Electronica Sinica, 2010, 38(2A): 213-217.DOI:
<FONT face=Verdana>Inspired by the research in physiology
a novel algorithm for extracting bottom-<FONT face=Verdana>up attention information (integration of contrast sensitivity and Markov chain
ACSMC) is proposed in this paper.In our algorithm
the original image is weighted with a contrast sensitivity formula which is a function retinal eccentricity to simulate the mechanism of retinal ganglion.A Markov chain is defined on feature maps.The equilibrium distribution of this chain is taken as saliency values.The <FONT face=Verdana>average of algorithm cost time and area under receiver operating characteristic curve (AUROC) based on the research of neurobiologist demonstrate its effectiveness.