Incorporating a Local Binary Fitting Model into a Maximum Regional Difference Model for Extracting Microscopic Information under Complex Conditions
Joint Authors
Guan, Qiu
Zhang, Jianwei
Chen, Min
Scalia, Massimo
Yao, Chunyan
Source
Mathematical Problems in Engineering
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-08-01
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
This paper presents a novel region-based method for extracting useful information from microscopic images under complex conditions.
It is especially used for blood cell segmentation and statistical analysis.
The active model detects several inner and outer contours of an object from its background.
The method incorporates a local binary fitting model into a maximum regional difference model.
It utilizes both local and global intensity information as the driving forces of the contour model on the principle of the largest regional difference.
The local and global fitting forces ensure that local dissimilarities can be captured and globally different areas can be segmented, respectively.
By combining the advantages of local and global information, the motion of the contour is driven by the mixed fitting force, which is composed of the local and global fitting term in the energy function.
Experiments are carried out in the laboratory, and results show that the novel model can yield good performances for microscopic image analysis.
American Psychological Association (APA)
Yao, Chunyan& Zhang, Jianwei& Chen, Min& Guan, Qiu& Scalia, Massimo. 2011. Incorporating a Local Binary Fitting Model into a Maximum Regional Difference Model for Extracting Microscopic Information under Complex Conditions. Mathematical Problems in Engineering،Vol. 2012, no. 2012, pp.1-10.
https://search.emarefa.net/detail/BIM-1029593
Modern Language Association (MLA)
Yao, Chunyan…[et al.]. Incorporating a Local Binary Fitting Model into a Maximum Regional Difference Model for Extracting Microscopic Information under Complex Conditions. Mathematical Problems in Engineering No. 2012 (2012), pp.1-10.
https://search.emarefa.net/detail/BIM-1029593
American Medical Association (AMA)
Yao, Chunyan& Zhang, Jianwei& Chen, Min& Guan, Qiu& Scalia, Massimo. Incorporating a Local Binary Fitting Model into a Maximum Regional Difference Model for Extracting Microscopic Information under Complex Conditions. Mathematical Problems in Engineering. 2011. Vol. 2012, no. 2012, pp.1-10.
https://search.emarefa.net/detail/BIM-1029593
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1029593