Image Enhancement Preprocessing for Improving Visual Localization and Mapping

Piran Fletcher; Aboozar Taherkhani; Nathanael L. Baisa

doi:10.1007/978-3-031-67192-0_30

Image Enhancement Preprocessing for Improving Visual Localization and Mapping

Piran Fletcher, Aboozar Taherkhani^*, Nathanael L. Baisa

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

Abstract

We present an enhancement to the ORB-SLAM3 visual localization and mapping algorithm for mobile robots that helps the algorithm to work in conditions of low light or rapid movement. We tested the practicality of the algorithm when used on a low-cost mobile robot platform with limited computational power. We successfully showed that image enhancement can improve the consistency of results in feature extraction and matching. The percentage of matched points between keyframes in the static tests was improved by up to 95% in light conditions and 57% in dark conditions. The image enhancement algorithms improved path quality by 50% - 70% in the rotational tests, and by up to 50% in the zig-zag path following tests. Image enhancement as a pre-feature extraction step in the ORB-SLAM3 algorithm therefore shows promise as a method to improve localization in conditions of low light or rapid movement.

Original language	English
Title of host publication	Intelligent and Fuzzy Systems
Subtitle of host publication	Intelligent Industrial Informatics and Efficient Networks Proceedings of the INFUS 2024 Conference, Volume 3
Editors	Cengiz Kahraman, Sezi Cevik Onar, Selcuk Cebi, Basar Oztaysi, Irem Ucal Sari, A. Cagrı Tolga
Publisher	Springer, Cham
Pages	240-246
Number of pages	7
Volume	3
ISBN (Electronic)	9783031671920
ISBN (Print)	9783031671913
DOIs	https://doi.org/10.1007/978-3-031-67192-0_30
Publication status	Published - 28 Aug 2024
Event	International Conference on Intelligent and Fuzzy Systems 2024 - Canakkale, Turkey Duration: 16 Jul 2024 → 18 Jul 2024 https://infus.itu.edu.tr/

Publication series

Name	Lecture Notes in Networks and Systems
Publisher	Springer Cham
Volume	1090
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	International Conference on Intelligent and Fuzzy Systems 2024
Abbreviated title	INFUS
Country/Territory	Turkey
City	Canakkale
Period	16/07/24 → 18/07/24
Internet address	https://infus.itu.edu.tr/

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

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10.1007/978-3-031-67192-0_30

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Fletcher, P., Taherkhani, A., & Baisa, N. L. (2024). Image Enhancement Preprocessing for Improving Visual Localization and Mapping. In C. Kahraman, S. Cevik Onar, S. Cebi, B. Oztaysi, I. Ucal Sari, & A. C. Tolga (Eds.), Intelligent and Fuzzy Systems: Intelligent Industrial Informatics and Efficient Networks Proceedings of the INFUS 2024 Conference, Volume 3 (Vol. 3, pp. 240-246). (Lecture Notes in Networks and Systems; Vol. 1090). Springer, Cham. https://doi.org/10.1007/978-3-031-67192-0_30

Fletcher, Piran ; Taherkhani, Aboozar ; Baisa, Nathanael L. / Image Enhancement Preprocessing for Improving Visual Localization and Mapping. Intelligent and Fuzzy Systems: Intelligent Industrial Informatics and Efficient Networks Proceedings of the INFUS 2024 Conference, Volume 3. editor / Cengiz Kahraman ; Sezi Cevik Onar ; Selcuk Cebi ; Basar Oztaysi ; Irem Ucal Sari ; A. Cagrı Tolga. Vol. 3 Springer, Cham, 2024. pp. 240-246 (Lecture Notes in Networks and Systems).

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title = "Image Enhancement Preprocessing for Improving Visual Localization and Mapping",

abstract = "We present an enhancement to the ORB-SLAM3 visual localization and mapping algorithm for mobile robots that helps the algorithm to work in conditions of low light or rapid movement. We tested the practicality of the algorithm when used on a low-cost mobile robot platform with limited computational power. We successfully showed that image enhancement can improve the consistency of results in feature extraction and matching. The percentage of matched points between keyframes in the static tests was improved by up to 95\% in light conditions and 57\% in dark conditions. The image enhancement algorithms improved path quality by 50\% - 70\% in the rotational tests, and by up to 50\% in the zig-zag path following tests. Image enhancement as a pre-feature extraction step in the ORB-SLAM3 algorithm therefore shows promise as a method to improve localization in conditions of low light or rapid movement.",

author = "Piran Fletcher and Aboozar Taherkhani and Baisa, \{Nathanael L.\}",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; International Conference on Intelligent and Fuzzy Systems 2024, INFUS ; Conference date: 16-07-2024 Through 18-07-2024",

year = "2024",

month = aug,

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language = "English",

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volume = "3",

series = "Lecture Notes in Networks and Systems",

publisher = "Springer, Cham",

pages = "240--246",

editor = "Cengiz Kahraman and \{Cevik Onar\}, Sezi and Selcuk Cebi and Basar Oztaysi and \{Ucal Sari\}, Irem and Tolga, \{A. Cagrı\}",

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Fletcher, P, Taherkhani, A & Baisa, NL 2024, Image Enhancement Preprocessing for Improving Visual Localization and Mapping. in C Kahraman, S Cevik Onar, S Cebi, B Oztaysi, I Ucal Sari & AC Tolga (eds), Intelligent and Fuzzy Systems: Intelligent Industrial Informatics and Efficient Networks Proceedings of the INFUS 2024 Conference, Volume 3. vol. 3, Lecture Notes in Networks and Systems, vol. 1090, Springer, Cham, pp. 240-246, International Conference on Intelligent and Fuzzy Systems 2024, Canakkale, Turkey, 16/07/24. https://doi.org/10.1007/978-3-031-67192-0_30

Image Enhancement Preprocessing for Improving Visual Localization and Mapping. / Fletcher, Piran; Taherkhani, Aboozar; Baisa, Nathanael L.
Intelligent and Fuzzy Systems: Intelligent Industrial Informatics and Efficient Networks Proceedings of the INFUS 2024 Conference, Volume 3. ed. / Cengiz Kahraman; Sezi Cevik Onar; Selcuk Cebi; Basar Oztaysi; Irem Ucal Sari; A. Cagrı Tolga. Vol. 3 Springer, Cham, 2024. p. 240-246 (Lecture Notes in Networks and Systems; Vol. 1090).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Image Enhancement Preprocessing for Improving Visual Localization and Mapping

AU - Fletcher, Piran

AU - Taherkhani, Aboozar

AU - Baisa, Nathanael L.

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

PY - 2024/8/28

Y1 - 2024/8/28

N2 - We present an enhancement to the ORB-SLAM3 visual localization and mapping algorithm for mobile robots that helps the algorithm to work in conditions of low light or rapid movement. We tested the practicality of the algorithm when used on a low-cost mobile robot platform with limited computational power. We successfully showed that image enhancement can improve the consistency of results in feature extraction and matching. The percentage of matched points between keyframes in the static tests was improved by up to 95% in light conditions and 57% in dark conditions. The image enhancement algorithms improved path quality by 50% - 70% in the rotational tests, and by up to 50% in the zig-zag path following tests. Image enhancement as a pre-feature extraction step in the ORB-SLAM3 algorithm therefore shows promise as a method to improve localization in conditions of low light or rapid movement.

AB - We present an enhancement to the ORB-SLAM3 visual localization and mapping algorithm for mobile robots that helps the algorithm to work in conditions of low light or rapid movement. We tested the practicality of the algorithm when used on a low-cost mobile robot platform with limited computational power. We successfully showed that image enhancement can improve the consistency of results in feature extraction and matching. The percentage of matched points between keyframes in the static tests was improved by up to 95% in light conditions and 57% in dark conditions. The image enhancement algorithms improved path quality by 50% - 70% in the rotational tests, and by up to 50% in the zig-zag path following tests. Image enhancement as a pre-feature extraction step in the ORB-SLAM3 algorithm therefore shows promise as a method to improve localization in conditions of low light or rapid movement.

UR - https://infus.itu.edu.tr/

U2 - 10.1007/978-3-031-67192-0_30

DO - 10.1007/978-3-031-67192-0_30

M3 - Conference Contribution (Conference Proceeding)

SN - 9783031671913

VL - 3

T3 - Lecture Notes in Networks and Systems

SP - 240

EP - 246

BT - Intelligent and Fuzzy Systems

A2 - Kahraman, Cengiz

A2 - Cevik Onar, Sezi

A2 - Cebi, Selcuk

A2 - Oztaysi, Basar

A2 - Ucal Sari, Irem

A2 - Tolga, A. Cagrı

PB - Springer, Cham

T2 - International Conference on Intelligent and Fuzzy Systems 2024

Y2 - 16 July 2024 through 18 July 2024

ER -

Fletcher P, Taherkhani A, Baisa NL. Image Enhancement Preprocessing for Improving Visual Localization and Mapping. In Kahraman C, Cevik Onar S, Cebi S, Oztaysi B, Ucal Sari I, Tolga AC, editors, Intelligent and Fuzzy Systems: Intelligent Industrial Informatics and Efficient Networks Proceedings of the INFUS 2024 Conference, Volume 3. Vol. 3. Springer, Cham. 2024. p. 240-246. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-67192-0_30

Image Enhancement Preprocessing for Improving Visual Localization and Mapping

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