Image stitching based on improved SURF algorithm

Jinxian Qi; Gongfa Li; Zhaojie Ju; Disi Chen; Du Jiang; Bo Tao; Guozhang Jiang; Ying Sun

doi:10.1007/978-3-030-27541-9_42

Image stitching based on improved SURF algorithm

Jinxian Qi, Gongfa Li, Zhaojie Ju, Disi Chen, Du Jiang, Bo Tao, Guozhang Jiang, Ying Sun

School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

In order to solve the problem of uneven distribution of picture features and stitching of images, an improved SURF feature extraction method is proposed. Image feature extraction and image registration are the core of image stitching, which is directly related to stitching quality. In this paper, a comprehensive and in-depth study of feature-based image registration is carried out, and an improved algorithm is proposed. Firstly, the Heisen detection operator in the SURF algorithm is introduced to realize feature detection, and the features are extracted as much as possible. Secondly, the characteristics are described by BRIEF operator in the ORB algorithm to realize the invariance of the rotation change. Then, the European pull distance is used to complete the similarity calculation, and the KNN algorithm is used to realize the feature rough matching. Finally, the distance threshold is used to remove the matching pair with larger distance, and then the RANSAC algorithm is used to complete the purification. Experiments show that the proposed algorithm has good real-time performance, strong robustness and high accuracy.

Original language	English
Title of host publication	Intelligent Robotics and Applications
Subtitle of host publication	12th International Conference, ICIRA 2019, Shenyang, China, August 8–11, 2019, Proceedings, Part V
Editors	Haibin Yu, Jinguo Liu, Lianqing Liu, Zhaojie Ju, Yuwang Liu, Dalin Zhou
Publisher	Springer
Chapter	42
Pages	515-527
Number of pages	13
ISBN (Electronic)	978-3-030-27541-9
ISBN (Print)	978-3-030-27540-2
DOIs	https://doi.org/10.1007/978-3-030-27541-9_42
Publication status	Published - 6 Aug 2019
Event	12th International Conference on Intelligent Robotics and Applications - Shenyang, China Duration: 8 Aug 2019 → 11 Aug 2019

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	11744
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Name	Lecture Notes in Artificial Intelligence
Publisher	Springer
Volume	11744
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	12th International Conference on Intelligent Robotics and Applications
Abbreviated title	ICIRA 2019
Country/Territory	China
City	Shenyang
Period	8/08/19 → 11/08/19

Keywords

image stitching
SURF algorithm
RANSAC

Access to Document

10.1007/978-3-030-27541-9_42

Qi_Image Stitching_ICIRA2019_313_final_v4
This is a post-peer-review, pre-copyedit version of an article published in Intelligent Robotics and Applications. ICIRA 2019. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-27541-9_42.
Accepted author manuscript (Post-print), 478 KB

Cite this

Qi, J., Li, G., Ju, Z., Chen, D., Jiang, D., Tao, B., Jiang, G., & Sun, Y. (2019). Image stitching based on improved SURF algorithm. In H. Yu, J. Liu, L. Liu, Z. Ju, Y. Liu, & D. Zhou (Eds.), Intelligent Robotics and Applications: 12th International Conference, ICIRA 2019, Shenyang, China, August 8–11, 2019, Proceedings, Part V (pp. 515-527). (Lecture Notes in Computer Science; Vol. 11744), (Lecture Notes in Artificial Intelligence; Vol. 11744). Springer. https://doi.org/10.1007/978-3-030-27541-9_42

Qi, Jinxian ; Li, Gongfa ; Ju, Zhaojie et al. / Image stitching based on improved SURF algorithm. Intelligent Robotics and Applications: 12th International Conference, ICIRA 2019, Shenyang, China, August 8–11, 2019, Proceedings, Part V. editor / Haibin Yu ; Jinguo Liu ; Lianqing Liu ; Zhaojie Ju ; Yuwang Liu ; Dalin Zhou. Springer, 2019. pp. 515-527 (Lecture Notes in Computer Science). (Lecture Notes in Artificial Intelligence).

@inproceedings{120a0e5fe9954a4bb25138bb1ef35d84,

title = "Image stitching based on improved SURF algorithm",

abstract = "In order to solve the problem of uneven distribution of picture features and stitching of images, an improved SURF feature extraction method is proposed. Image feature extraction and image registration are the core of image stitching, which is directly related to stitching quality. In this paper, a comprehensive and in-depth study of feature-based image registration is carried out, and an improved algorithm is proposed. Firstly, the Heisen detection operator in the SURF algorithm is introduced to realize feature detection, and the features are extracted as much as possible. Secondly, the characteristics are described by BRIEF operator in the ORB algorithm to realize the invariance of the rotation change. Then, the European pull distance is used to complete the similarity calculation, and the KNN algorithm is used to realize the feature rough matching. Finally, the distance threshold is used to remove the matching pair with larger distance, and then the RANSAC algorithm is used to complete the purification. Experiments show that the proposed algorithm has good real-time performance, strong robustness and high accuracy.",

keywords = "image stitching, SURF algorithm, RANSAC",

author = "Jinxian Qi and Gongfa Li and Zhaojie Ju and Disi Chen and Du Jiang and Bo Tao and Guozhang Jiang and Ying Sun",

year = "2019",

month = aug,

day = "6",

doi = "10.1007/978-3-030-27541-9_42",

language = "English",

isbn = "978-3-030-27540-2",

series = "Lecture Notes in Computer Science",

publisher = "Springer",

pages = "515--527",

editor = "Haibin Yu and Jinguo Liu and Lianqing Liu and Zhaojie Ju and Yuwang Liu and Dalin Zhou",

booktitle = "Intelligent Robotics and Applications",

note = "12th International Conference on Intelligent Robotics and Applications, ICIRA 2019 ; Conference date: 08-08-2019 Through 11-08-2019",

}

Qi, J, Li, G, Ju, Z, Chen, D, Jiang, D, Tao, B, Jiang, G & Sun, Y 2019, Image stitching based on improved SURF algorithm. in H Yu, J Liu, L Liu, Z Ju, Y Liu & D Zhou (eds), Intelligent Robotics and Applications: 12th International Conference, ICIRA 2019, Shenyang, China, August 8–11, 2019, Proceedings, Part V. Lecture Notes in Computer Science, vol. 11744, Lecture Notes in Artificial Intelligence, vol. 11744, Springer, pp. 515-527, 12th International Conference on Intelligent Robotics and Applications, Shenyang, China, 8/08/19. https://doi.org/10.1007/978-3-030-27541-9_42

Image stitching based on improved SURF algorithm. / Qi, Jinxian; Li, Gongfa; Ju, Zhaojie et al.
Intelligent Robotics and Applications: 12th International Conference, ICIRA 2019, Shenyang, China, August 8–11, 2019, Proceedings, Part V. ed. / Haibin Yu; Jinguo Liu; Lianqing Liu; Zhaojie Ju; Yuwang Liu; Dalin Zhou. Springer, 2019. p. 515-527 (Lecture Notes in Computer Science; Vol. 11744), (Lecture Notes in Artificial Intelligence; Vol. 11744).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Image stitching based on improved SURF algorithm

AU - Qi, Jinxian

AU - Li, Gongfa

AU - Ju, Zhaojie

AU - Chen, Disi

AU - Jiang, Du

AU - Tao, Bo

AU - Jiang, Guozhang

AU - Sun, Ying

PY - 2019/8/6

Y1 - 2019/8/6

N2 - In order to solve the problem of uneven distribution of picture features and stitching of images, an improved SURF feature extraction method is proposed. Image feature extraction and image registration are the core of image stitching, which is directly related to stitching quality. In this paper, a comprehensive and in-depth study of feature-based image registration is carried out, and an improved algorithm is proposed. Firstly, the Heisen detection operator in the SURF algorithm is introduced to realize feature detection, and the features are extracted as much as possible. Secondly, the characteristics are described by BRIEF operator in the ORB algorithm to realize the invariance of the rotation change. Then, the European pull distance is used to complete the similarity calculation, and the KNN algorithm is used to realize the feature rough matching. Finally, the distance threshold is used to remove the matching pair with larger distance, and then the RANSAC algorithm is used to complete the purification. Experiments show that the proposed algorithm has good real-time performance, strong robustness and high accuracy.

AB - In order to solve the problem of uneven distribution of picture features and stitching of images, an improved SURF feature extraction method is proposed. Image feature extraction and image registration are the core of image stitching, which is directly related to stitching quality. In this paper, a comprehensive and in-depth study of feature-based image registration is carried out, and an improved algorithm is proposed. Firstly, the Heisen detection operator in the SURF algorithm is introduced to realize feature detection, and the features are extracted as much as possible. Secondly, the characteristics are described by BRIEF operator in the ORB algorithm to realize the invariance of the rotation change. Then, the European pull distance is used to complete the similarity calculation, and the KNN algorithm is used to realize the feature rough matching. Finally, the distance threshold is used to remove the matching pair with larger distance, and then the RANSAC algorithm is used to complete the purification. Experiments show that the proposed algorithm has good real-time performance, strong robustness and high accuracy.

KW - image stitching

KW - SURF algorithm

KW - RANSAC

U2 - 10.1007/978-3-030-27541-9_42

DO - 10.1007/978-3-030-27541-9_42

M3 - Conference contribution

SN - 978-3-030-27540-2

T3 - Lecture Notes in Computer Science

SP - 515

EP - 527

BT - Intelligent Robotics and Applications

A2 - Yu, Haibin

A2 - Liu, Jinguo

A2 - Liu, Lianqing

A2 - Ju, Zhaojie

A2 - Liu, Yuwang

A2 - Zhou, Dalin

PB - Springer

T2 - 12th International Conference on Intelligent Robotics and Applications

Y2 - 8 August 2019 through 11 August 2019

ER -

Qi J, Li G, Ju Z, Chen D, Jiang D, Tao B et al. Image stitching based on improved SURF algorithm. In Yu H, Liu J, Liu L, Ju Z, Liu Y, Zhou D, editors, Intelligent Robotics and Applications: 12th International Conference, ICIRA 2019, Shenyang, China, August 8–11, 2019, Proceedings, Part V. Springer. 2019. p. 515-527. (Lecture Notes in Computer Science). (Lecture Notes in Artificial Intelligence). doi: 10.1007/978-3-030-27541-9_42

Image stitching based on improved SURF algorithm

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Keywords

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