Underwater Object Recognition Using Transformable Template Matching Based on Prior Knowledge
Joint Authors
Han, Zhi
Tang, Yandong
Wu, Chengdong
Zhu, Jianjiang
Yu, Siquan
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-02-03
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Underwater object recognition in sonar images, such as mine detection and wreckage detection of a submerged airplane, is a very challenging task.
The main difficulties include but are not limited to object rotation, confusion from false targets and complex backgrounds, and extensibility of recognition ability on diverse types of objects.
In this paper, we propose an underwater object detection and recognition method using a transformable template matching approach based on prior knowledge.
Specifically, we first extract features and construct a template from sonar video sequences based on the analysis of acoustic shadows and highlight regions.
Then, we identify the target region in the objective image by fast saliency detection techniques based on FFT, which can significantly improve efficiency by avoiding an exhaustive global search.
After affine transformation of the template according to the orientation of the target, we extract normalized gradient features and calculate the similarity between the template and the target region, which can solve various difficulties mentioned above using only one template.
Experimental results demonstrate that the proposed method can well recognize different underwater objects, such as mine-like objects and triangle-like objects and can satisfy the demands of real-time application.
American Psychological Association (APA)
Zhu, Jianjiang& Yu, Siquan& Han, Zhi& Tang, Yandong& Wu, Chengdong. 2019. Underwater Object Recognition Using Transformable Template Matching Based on Prior Knowledge. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1194941
Modern Language Association (MLA)
Zhu, Jianjiang…[et al.]. Underwater Object Recognition Using Transformable Template Matching Based on Prior Knowledge. Mathematical Problems in Engineering No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1194941
American Medical Association (AMA)
Zhu, Jianjiang& Yu, Siquan& Han, Zhi& Tang, Yandong& Wu, Chengdong. Underwater Object Recognition Using Transformable Template Matching Based on Prior Knowledge. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1194941
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1194941