A distribution prior model for airplane segmentation without exact template

In many practical applications of image segmentation problems, employing prior information can greatly improve seg-mentation results. This paper continues to study one kind of prior information, called prior distribution. Within this research, there is no exact template of the object; instead only s...

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Bibliographic Details
Published in:Journal of systems engineering and electronics 2020-02, Vol.31 (1), p.56-63
Main Author: DAI, Ming
Format: Article
Language:English
Online Access:Get full text
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Summary:In many practical applications of image segmentation problems, employing prior information can greatly improve seg-mentation results. This paper continues to study one kind of prior information, called prior distribution. Within this research, there is no exact template of the object; instead only several samples are given. The proposed method, called the parametric distribution prior model, extends our previous model by adding the training procedure to learn the prior distribution of the objects. Then this paper establishes the energy function of the active contour model (ACM) with consideration of this parametric form of prior distribu-tion. Therefore, during the process of segmenting, the template can update itself while the contour evolves. Experiments are per-formed on the airplane data set. Experimental results demonstrate the potential of the proposed method that with the information of prior distribution, the segmentation effect and speed can be both improved efficaciously.
ISSN:1004-4132
DOI:10.21629/JSEE.2020.01.07