Selective Feature Fusion Based Adaptive Image Segmentation Algorithm
Joint Authors
Li, Qianwen
Shen, Wen
Wei, Zhihua
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-09-09
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
Image segmentation is an essential task in computer vision and pattern recognition.
There are two key challenges for image segmentation.
One is to find the most discriminative image feature set to get high-quality segments.
The other is to achieve good performance among various images.
In this paper, we firstly propose a selective feature fusion algorithm to choose the best feature set by evaluating the results of presegmentation.
Specifically, the proposed method fuses selected features and applies the fused features to region growing segmentation algorithm.
To get better segments on different images, we further develop an algorithm to change threshold adaptively for each image by measuring the size of the region.
The adaptive threshold can achieve better performance on each image than fixed threshold.
Experimental results demonstrate that our method improves the performance of traditional region growing by selective feature fusion and adaptive threshold.
Moreover, our proposed algorithm obtains promising results and outperforms some popular approaches.
American Psychological Association (APA)
Li, Qianwen& Wei, Zhihua& Shen, Wen. 2018. Selective Feature Fusion Based Adaptive Image Segmentation Algorithm. Advances in Multimedia،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1118439
Modern Language Association (MLA)
Li, Qianwen…[et al.]. Selective Feature Fusion Based Adaptive Image Segmentation Algorithm. Advances in Multimedia No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1118439
American Medical Association (AMA)
Li, Qianwen& Wei, Zhihua& Shen, Wen. Selective Feature Fusion Based Adaptive Image Segmentation Algorithm. Advances in Multimedia. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1118439
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1118439