{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T13:15:04Z","timestamp":1775913304333,"version":"3.50.1"},"reference-count":53,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2019,11,1]],"date-time":"2019-11-01T00:00:00Z","timestamp":1572566400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The regular inspection of underground facilities such as pipelines is absolutely essential. Pipeline leakage caused by corrosion and deformation must be detected in time, otherwise, it may cause fatal disasters for human beings. In our previous research, a robot chain system (RCS) based on visible light relay communication (VLRC) for pipe inspection has been developed. This system can basically realize the light-based transmission of control command signals and illuminance-based coordinated movement, whereas the collection and transmission approach of the pipe leakage image have not been studied. Compared with former in-pipe wireless communication techniques, VLRC can not only overcome the instability and inefficiency of in-pipe data transmission but also extend the communication range with high transmission rates. The most important feature is that it can provide a stable illumination and high-quality communication for pipe inspection robot and finally improve the energy efficiency. Hence, the aim of this article is to analyze the performance of VLRC-based image transmission in the pipe and in the future provide a high-quality, long-range, and high-efficiency image transmission for complex infrastructure inspection with RCS. The transmission systems based on two signal transmission modes analog image signal relay transmission (AISRT) and digital image frame relay transmission (DIFRT) have been proposed. Multiple experiments including the waveform test, the test of transmission features with different bit error rate (BER), and in the different mediums were conducted between these two systems. The experiment revealed that DIFRT was superior to the AISRT in terms of the relatively high-quality image transmission and reconstruction quality. It could better overcome the attenuation brought by the absorption and scattering effects and finally increased the transmission range than former communication methods. The DIFRT system could also operate at 50     kbps     with relatively low BER whether in the air or water. The technique in this research could potentially provide a new strategy for implementations in the stable, effective, high-speed, and long-range image transmission of the robots in some other special environments such as tunnel, mine, and underwater, etc.<\/jats:p>","DOI":"10.3390\/s19214760","type":"journal-article","created":{"date-parts":[[2019,11,1]],"date-time":"2019-11-01T12:30:50Z","timestamp":1572611450000},"page":"4760","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["A Preliminary Experimental Analysis of In-Pipe Image Transmission Based on Visible Light Relay Communication"],"prefix":"10.3390","volume":"19","author":[{"given":"Wen","family":"Zhao","sequence":"first","affiliation":[{"name":"Graduate School of Creative Science and Engineering, Waseda University, Tokyo 169-8050, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mitsuhiro","family":"Kamezaki","sequence":"additional","affiliation":[{"name":"Graduate School of Creative Science and Engineering, Waseda University, Tokyo 169-8050, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaoru","family":"Yamaguchi","sequence":"additional","affiliation":[{"name":"Graduate School of Creative Science and Engineering, Waseda University, Tokyo 169-8050, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minoru","family":"Konno","sequence":"additional","affiliation":[{"name":"Tokyo Gas Co. Ltd., Tokyo 105-8527, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Akihiko","family":"Onuki","sequence":"additional","affiliation":[{"name":"Tokyo Gas Co. Ltd., Tokyo 105-8527, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shigeki","family":"Sugano","sequence":"additional","affiliation":[{"name":"Graduate School of Creative Science and Engineering, Waseda University, Tokyo 169-8050, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Mills, G.H., Jackson, A.E., and Richardson., R.C. (2017). Advances in the inspection of unpiggable pipelines. Robotics, 6.","DOI":"10.3390\/robotics6040036"},{"key":"ref_2","first-page":"3","article-title":"Anomaly pre-localization in distribution\u2013transmission mains by pump trip: Preliminary field tests in the Milan pipe system","volume":"17","author":"Meniconi","year":"2015","journal-title":"J. Hydro. Infor."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1016\/j.jher.2009.02.003","article-title":"A selective literature review of transient-based leak detection methods","volume":"2","author":"Colombo","year":"2009","journal-title":"J. Hydro. Envir. Res."},{"key":"ref_4","unstructured":"Haddar, M., Bartelmus, W., Chaari, F., and Zimroz, R. (2016). Modeling and Monitoring of Pipelines and Networks, Springer Nature."},{"key":"ref_5","first-page":"302","article-title":"Localization techniques for water pipeline leakages: A review","volume":"7","author":"Lah","year":"2018","journal-title":"Int. J. Integr. Eng."},{"key":"ref_6","unstructured":"Du, Y., Zhu, Q., Ghauri, S., Zhai, J., Jia, H., and Nouri, H. (2012, January 24\u201326). Progresses in study of pipeline robot. Proceedings of the IEEE International Conference on Modelling, Identification, and Control (ICMIC), Wuhan, China."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Rostami, J., Tse, P.W.T., and Fang, Z. (2017). Sparse and dispersion-based matching pursuit for minimizing the dispersion effect occurring when using guided wave for pipe inspection. Materials, 10.","DOI":"10.3390\/ma10060622"},{"key":"ref_8","unstructured":"Masuta, H., Watanabe, H., Sato, K., and Lim, H. (November, January 31). Recognition of branch pipe for pipe inspection robot using fiber grating vision sensor. Proceedings of the IEEE International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), Jeju, Korea."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"875","DOI":"10.1016\/j.autcon.2010.06.001","article-title":"A morphological approach to pipe image interpretation based on segmentation by support vector machine","volume":"19","author":"Mashford","year":"2010","journal-title":"Autom. Constr."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1016\/j.engfailanal.2019.04.062","article-title":"Inspection of internal erosion-corrosion of elbow pipe in the desalination station","volume":"102","author":"Muthannaa","year":"2019","journal-title":"Eng. Fail. Anal."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Zhao, W., Kamezaki, M., Yoshida, K., Konno, M., Onuki, A., and Sugano, S. (2019, January 14\u201316). A preliminary experimental study on control technology of pipeline robots based on visible light communication. Proceedings of the IEEE\/SICE International Symposium on System Integration (SII), Paris, France.","DOI":"10.1109\/SII.2019.8700337"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Zhao, W., Kamezaki, M., Yoshida., K., Konno, M., Onuki, A., and Sugano, S. (2019). A coordinated wheeled gas pipeline robot chain system based on visible light relay communication and illuminance assessment. Sensors, 19.","DOI":"10.3390\/s19102322"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Png, L.C. (2013, January 3\u20136). A fully integrated audio, video, and data VLC transceiver system for smartphones and tablets. Proceedings of the IEEE International Symposium on Consumer Electronics (ISCE), Hsinchu, Taiwan.","DOI":"10.1109\/ISCE.2013.6570210"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Doniec, M., Xu, A., and Rus, D. (2013, January 6\u201310). Robust real-time underwater digital video streaming using optical communication. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany.","DOI":"10.1109\/ICRA.2013.6631308"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Narmanlioglu, O., Turan, B., Kebapci, B., Ergen, S.C., and Uysal, M. (2016, January 8\u201310). Poster: On-board camera video transmission over vehicular VLC. Proceedings of the IEEE Vehicular Networking Conference (VNC), Columbus, OH, USA.","DOI":"10.1109\/VNC.2016.7835950"},{"key":"ref_16","first-page":"2322","article-title":"Optical-acoustic hybrid network toward real-time video streaming for mobile underwater sensors","volume":"19","author":"Han","year":"2019","journal-title":"Ad Hoc Netw."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.image.2017.02.001","article-title":"A survey of design and implementation for optical camera communication","volume":"53","author":"Lea","year":"2017","journal-title":"Signal. Process. Image Commun."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"10738","DOI":"10.3390\/s111110738","article-title":"Sensor network architectures for monitoring underwater pipelines","volume":"11","author":"Mohamed","year":"2011","journal-title":"Sensors"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Eren, F., Peeri, S., Thein, M.W., Rzhanov, Y., Celikkol, B., and Swift, M.R. (2017). Position, orientation and velocity detection of unmanned underwater vehicles (UUVs) using an optical detector array. Sensors, 17.","DOI":"10.3390\/s17081741"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Liu, Y.F., Jiang, Z.H., Wang, F.M., and Chi, N. (2018, January 1\u20132). 315 Mbps internet of vehicle communication system using car head lamp based on weighted pre-distortion. Proceedings of the IEEE International Conference on Communication Technology, Chongqing, China.","DOI":"10.1109\/ICCT.2018.8599895"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Sticklus, J., Hieronymi, M., and Hoeher., P.A. (2018). Effects and constraints of optical filtering on ambient light suppression in LED-based underwater communications. Sensors, 18.","DOI":"10.3390\/s18113710"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Sendra, S., Lloret, J., Gardel, A., Jimenez, J.M., and Rodrigues, J.J.P.C. (2016). Underwater communications for video surveillance systems at 2.4 GHz. Sensors, 16.","DOI":"10.3390\/s16101769"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"14647","DOI":"10.3390\/s121114647","article-title":"Energy efficient image\/video data transmission on commercial multi-core processors","volume":"12","author":"Lee","year":"2012","journal-title":"Sensors"},{"key":"ref_24","first-page":"5518","article-title":"Comparison of image quality assessment: PSNR, HVS, SSIM, UIQI","volume":"3","author":"Soong","year":"2012","journal-title":"Inter. J. Sci. Eng. Res."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Hore, A., and Ziou, D. (2010, January 23\u201326). Image quality metrics: PSNR vs SSIM. In Proceedings of the International Conference on Pattern Recognition (ICPR), Istanbul, Turkey.","DOI":"10.1109\/ICPR.2010.579"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.compind.2018.03.020","article-title":"Utilizing text recognition for the defects extraction in sewers CCTV inspection videos","volume":"99","author":"Dang","year":"2018","journal-title":"Comp. Indus."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3562","DOI":"10.1016\/j.eswa.2008.02.006","article-title":"Segmenting ideal morphologies of sewer pipe defects on CCTV images for automated diagnosis","volume":"36","author":"Yang","year":"2009","journal-title":"Expert Sys. Appl."},{"key":"ref_28","unstructured":"Cree Inc. (2018). Cree XLamp XHP70 LEDs, Product Family Data Sheet, CLD-DS114 Rev 1K, 2014\u20142018, Cree, Inc."},{"key":"ref_29","unstructured":"Thorlabs, Inc. (2016). PDA10A(-EC) Si Amplified Fixed Gain Detector, User Guide, Thorlabs, Inc."},{"key":"ref_30","unstructured":"Mini-Circuits, Inc. (2018). ZHL-6A-S+, Broadband AMPL\/BNC, REV. HM162646 2018, Mini-Circuits, Inc."},{"key":"ref_31","unstructured":"Huaxin Tech Inc. (2015). KPATT2.5-90\/1S-2N, Key-Press Attenuator 0-90 dB, Rev J, 2015, Huaxin Tech Inc."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.optcom.2019.01.047","article-title":"Hybrid modulation scheme for visible light communication using CMOS camera","volume":"440","author":"Xu","year":"2019","journal-title":"Opt. Commun."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"4133","DOI":"10.3390\/s120404133","article-title":"Differential binary encoding method for calibrating image sensors based on IOFBs","volume":"12","author":"Fernandez","year":"2012","journal-title":"Sensors"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Zhao, D.F., Tian, H., and Xue, R. (2019). Adaptive rate-compatible non-Binary LDPC coding scheme for the B5G mobile system. Sensors, 19.","DOI":"10.3390\/s19051067"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Jridi, M., Chapel, T., Dorez, V., Bougeant, G.L., and Botlan, A.L. (2018). SoC-based edge computing gateway in the context of the internet of multimedia things: Experimental platform. J. Low Power Electron. Appl., 8.","DOI":"10.3390\/jlpea8010001"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Pan, T.M., Fan, K.C., and Wang., Y.K. (2019). Object-based approach for adaptive source coding of surveillance video. Appl. Sci., 9.","DOI":"10.3390\/app9102003"},{"key":"ref_37","first-page":"1972","article-title":"Visual IoT security: Data hiding in AMBTC images using block-wise embedding strategy","volume":"19","author":"Lin","year":"2019","journal-title":"Sensors"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.image.2018.09.009","article-title":"A framework for computationally efficient video quality assessment","volume":"70","author":"Akamine","year":"2019","journal-title":"Signal. Process. Image Commun."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.neucom.2018.04.072","article-title":"Stereoscopic video quality assessment based on 3D convolutional neural networks","volume":"309","author":"Yang","year":"2018","journal-title":"Neurocomputing"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.bspc.2016.02.006","article-title":"Review of medical image quality assessment","volume":"27","author":"Chow","year":"2016","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1016\/j.patrec.2016.07.002","article-title":"Enhanced analysis of thermographic images for monitoring of district heat pipe networks","volume":"83","author":"Berg","year":"2016","journal-title":"Lett. Pattern Recognit."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.autcon.2005.02.007","article-title":"Segmentation of buried concrete pipe images","volume":"15","author":"Sinh","year":"2006","journal-title":"Autom. Constr."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.autcon.2018.08.006","article-title":"Automated detection of sewer pipe defects in closed-circuit television images using deep learning techniques","volume":"95","author":"Cheng","year":"2018","journal-title":"Autom. Constr."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"904","DOI":"10.1016\/j.compeleceng.2017.12.006","article-title":"An imaging-inspired no-reference underwater color image quality assessment metric","volume":"70","author":"Wang","year":"2018","journal-title":"Comput. Electr. Eng."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.image.2018.09.005","article-title":"Perceptual image quality assessment through spectral analysis of error representations","volume":"70","author":"Temel","year":"2019","journal-title":"Signal Process. Image Commun."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.ijleo.2018.08.136","article-title":"Employment of the appropriate range of sawtooth-shaped-function illumination intensity to improve the image quality","volume":"175","author":"Yu","year":"2018","journal-title":"Optik"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1016\/j.ijleo.2018.02.101","article-title":"Automatic focus and fusion image algorithm using nonlinear correlation: Image quality evaluation","volume":"164","author":"Marin","year":"2018","journal-title":"Optik"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.image.2019.04.007","article-title":"Linking visual saliency deviation to image quality degradation: A saliency deviation-based image quality index","volume":"75","author":"Zhang","year":"2019","journal-title":"Signal Process. Image Commun."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1016\/j.compeleceng.2016.08.014","article-title":"Image quality assessment via spatial structural analysis","volume":"70","author":"Yang","year":"2018","journal-title":"Comp. Electr. Eng."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1016\/j.jvcir.2018.12.005","article-title":"Blind image quality assessment with hierarchy: Degradation from local structure to deep semantics","volume":"58","author":"Wu","year":"2019","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.jvcir.2018.10.018","article-title":"Efficient VR video representation and quality assessment","volume":"57","author":"Wu","year":"2018","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Agarwal, S. (2018). Secure image transmission using fractal and 2D-chaotic map. Imaging, 4.","DOI":"10.3390\/jimaging4010017"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1016\/j.image.2010.03.006","article-title":"Modelling of spatio\u2013temporal interaction for video quality assessment","volume":"25","author":"Thu","year":"2010","journal-title":"Signal Process. Image Commun."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/21\/4760\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:31:21Z","timestamp":1760189481000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/21\/4760"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,1]]},"references-count":53,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2019,11]]}},"alternative-id":["s19214760"],"URL":"https:\/\/doi.org\/10.3390\/s19214760","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,11,1]]}}}