Title:	EXTRACTION METHOD OF KEYPOINT DESCRIPTOR FOR OBJECT RECOGNITION IN SONAR IMAGE
Author(s):	Jeong Mun Park, Wan-Jin Kim and Kun Su Yoon
ISBN:	978-989-8533-79-1
Editors:	Katherine Blashki and Yingcai Xiao
Year:	2018
Edition:	Single
Keywords:	Object Recognition, Keypoint Descriptor, Scale invariant Feature Transform
Type:	Full Paper
First Page:	261
Last Page:	268
Language:	English
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Paper Abstract:	In sonar images, the object shape is often distorted by the external conditions such as sedimentation, pulse repetition interval, ship speed, and redirection, which is generally modeled as the affine transform. Scale invariant feature transform(SIFT) and pyramid-SIFT(p-SIFT) are known as a good solution to the scale and rotation variance. However, these methods are vulnerable to the shearing problem. To solve the affine problem in sonar imaging systems, we propose a new keypoint descriptor extraction method. The proposed method generates multiple keypoint descriptors based on affine transformed images, and picks out effective keypoint descriptors. Test results show that the proposed method, in terms of recognition rate, has better accuracy than those of the conventional methods for scaling of x, y-axis, rotation, and shearing cases. The average improved accuracy rate of SIFT and p-SIFT is 7% and 4%, respectively.
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