A Novel Python Video Processing Program for Identifying and Quantification of Soil Cracks in Real Time

Vaibhav Khandare Dilip; He Huang; Ankit Garg; Xilong Huang; Guoxiong Mei

doi:10.1007/978-981-16-6407-6_4

A Novel Python Video Processing Program for Identifying and Quantification of Soil Cracks in Real Time

Vaibhav Khandare Dilip^*, He Huang, Ankit Garg, Xilong Huang, Guoxiong Mei

^*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

Abstract

The presence of soil cracks can lead to higher rainfall water infiltration, which will in turn cause instability in ground engineering infrastructure. Maintenance of ground infrastructure is hence essential, and such cracks are often identified through manual observations, that are laborious and not easily quantifiable. One of the ways could be to develop an automated program that can capture cracks through video processing. The objective of this study is to develop a simple video processing technique for soil crack sorting and its quantification in real-time. The new program automates the sorting of a region of cracks according to the given boundaries and quantifies the number of cracks in that region. A stepwise strategy is demonstrated to efficiently sort cracks and compute the crack intensity factor of real-time video with a negligible delay. Python script takes a frame from a video and analyzes it. It first automatically extracts the required portion of a video and computes cracks in this region. It also identifies the frames which have cracks and gives corresponding time and location to the administrator. Such a program can be useful in the future for analyzing videos obtained from UAV monitoring of the large area and, thus, identify vulnerable areas for maintenance.

Original language	English
Title of host publication	Proceedings of the 2nd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications - ICMISC 2021
Editors	Vinit Kumar Gunjan, Jacek M. Zurada
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	39-46
Number of pages	8
ISBN (Print)	9789811664069
DOIs	https://doi.org/10.1007/978-981-16-6407-6_4
Publication status	Published - 2022
Externally published	Yes
Event	2nd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications, ICMISC 2021 - Hyderabad, India Duration: 28 Mar 2021 → 29 Mar 2021

Publication series

Name	Lecture Notes in Networks and Systems
Volume	237
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	2nd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications, ICMISC 2021
Country/Territory	India
City	Hyderabad
Period	28/03/21 → 29/03/21

Keywords

Automation
Cost-effective
Cracks quantification
Python script
Region isolation

Access to Document

10.1007/978-981-16-6407-6_4

Cite this

Dilip, V. K., Huang, H., Garg, A., Huang, X., & Mei, G. (2022). A Novel Python Video Processing Program for Identifying and Quantification of Soil Cracks in Real Time. In V. K. Gunjan, & J. M. Zurada (Eds.), Proceedings of the 2nd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications - ICMISC 2021 (pp. 39-46). (Lecture Notes in Networks and Systems; Vol. 237). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-16-6407-6_4

Dilip, Vaibhav Khandare ; Huang, He ; Garg, Ankit et al. / A Novel Python Video Processing Program for Identifying and Quantification of Soil Cracks in Real Time. Proceedings of the 2nd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications - ICMISC 2021. editor / Vinit Kumar Gunjan ; Jacek M. Zurada. Springer Science and Business Media Deutschland GmbH, 2022. pp. 39-46 (Lecture Notes in Networks and Systems).

@inproceedings{fe171a9a468a4f39a9d9c15922be28bd,

title = "A Novel Python Video Processing Program for Identifying and Quantification of Soil Cracks in Real Time",

abstract = "The presence of soil cracks can lead to higher rainfall water infiltration, which will in turn cause instability in ground engineering infrastructure. Maintenance of ground infrastructure is hence essential, and such cracks are often identified through manual observations, that are laborious and not easily quantifiable. One of the ways could be to develop an automated program that can capture cracks through video processing. The objective of this study is to develop a simple video processing technique for soil crack sorting and its quantification in real-time. The new program automates the sorting of a region of cracks according to the given boundaries and quantifies the number of cracks in that region. A stepwise strategy is demonstrated to efficiently sort cracks and compute the crack intensity factor of real-time video with a negligible delay. Python script takes a frame from a video and analyzes it. It first automatically extracts the required portion of a video and computes cracks in this region. It also identifies the frames which have cracks and gives corresponding time and location to the administrator. Such a program can be useful in the future for analyzing videos obtained from UAV monitoring of the large area and, thus, identify vulnerable areas for maintenance.",

keywords = "Automation, Cost-effective, Cracks quantification, Python script, Region isolation",

author = "Dilip, {Vaibhav Khandare} and He Huang and Ankit Garg and Xilong Huang and Guoxiong Mei",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 2nd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications, ICMISC 2021 ; Conference date: 28-03-2021 Through 29-03-2021",

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doi = "10.1007/978-981-16-6407-6_4",

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series = "Lecture Notes in Networks and Systems",

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Dilip, VK, Huang, H, Garg, A, Huang, X & Mei, G 2022, A Novel Python Video Processing Program for Identifying and Quantification of Soil Cracks in Real Time. in VK Gunjan & JM Zurada (eds), Proceedings of the 2nd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications - ICMISC 2021. Lecture Notes in Networks and Systems, vol. 237, Springer Science and Business Media Deutschland GmbH, pp. 39-46, 2nd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications, ICMISC 2021, Hyderabad, India, 28/03/21. https://doi.org/10.1007/978-981-16-6407-6_4

A Novel Python Video Processing Program for Identifying and Quantification of Soil Cracks in Real Time. / Dilip, Vaibhav Khandare; Huang, He; Garg, Ankit et al.
Proceedings of the 2nd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications - ICMISC 2021. ed. / Vinit Kumar Gunjan; Jacek M. Zurada. Springer Science and Business Media Deutschland GmbH, 2022. p. 39-46 (Lecture Notes in Networks and Systems; Vol. 237).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

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AU - Mei, Guoxiong

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Dilip VK, Huang H, Garg A, Huang X, Mei G. A Novel Python Video Processing Program for Identifying and Quantification of Soil Cracks in Real Time. In Gunjan VK, Zurada JM, editors, Proceedings of the 2nd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications - ICMISC 2021. Springer Science and Business Media Deutschland GmbH. 2022. p. 39-46. (Lecture Notes in Networks and Systems). doi: 10.1007/978-981-16-6407-6_4

A Novel Python Video Processing Program for Identifying and Quantification of Soil Cracks in Real Time

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