{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T19:42:50Z","timestamp":1760902970213,"version":"build-2065373602"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032060068","type":"print"},{"value":"9783032060075","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T00:00:00Z","timestamp":1760918400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T00:00:00Z","timestamp":1760918400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-06007-5_8","type":"book-chapter","created":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T19:03:22Z","timestamp":1760900602000},"page":"123-146","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Tree Ring Detection for\u00a0Raw Wood Cross-Section Image Analysis"],"prefix":"10.1007","author":[{"given":"R\u00e9mi","family":"Decelle","sequence":"first","affiliation":[]},{"given":"Phuc","family":"Ngo","sequence":"additional","affiliation":[]},{"given":"Isabelle","family":"Debled-Rennesson","sequence":"additional","affiliation":[]},{"given":"Fr\u00e9d\u00e9ric","family":"Mothe","sequence":"additional","affiliation":[]},{"given":"Fleur","family":"Longuetaud","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,10,20]]},"reference":[{"key":"8_CR1","doi-asserted-by":"crossref","unstructured":"Abhishek, K., Hamarneh, G.: Matthews correlation coefficient loss for deep convolutional networks: application to skin lesion segmentation. In: 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), pp. 225\u2013229. IEEE (2021)","DOI":"10.1109\/ISBI48211.2021.9433782"},{"key":"8_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s41747-020-00200-2","volume":"5","author":"OU Aydin","year":"2021","unstructured":"Aydin, O.U., et al.: On the usage of average hausdorff distance for segmentation performance assessment: hidden error when used for ranking. European Radiol. Exper. 5, 1\u20137 (2021)","journal-title":"European Radiol. Exper."},{"key":"8_CR3","doi-asserted-by":"crossref","unstructured":"Berenstein, C.A., Lavine, D.: On the number of digital straight line segments. IEEE Trans. Pattern Anal. Mach. Intell. 10(6), 880\u2013887 (1988)","DOI":"10.1109\/34.9109"},{"key":"8_CR4","unstructured":"Chen, L.C., Papandreou, G., Schroff, F., Adam, H.: Rethinking Atrous convolution for semantic image segmentation. arXiv preprint arXiv:1706.05587 (2017)"},{"key":"8_CR5","doi-asserted-by":"crossref","unstructured":"Chen, L.C., Zhu, Y., Papandreou, G., Schroff, F., Adam, H.: Encoder-decoder with Atrous separable convolution for semantic image segmentation. In: Proceedings of ECCV, pp. 801\u2013818 (2018)","DOI":"10.1007\/978-3-030-01234-2_49"},{"key":"8_CR6","doi-asserted-by":"crossref","unstructured":"Conner, W.S., Schowengerdt, R.A., Munro, M., Hughes, M.K.: Design of a computer vision based tree ring dating system. In: IEEE Southwest Symposium on Image Analysis and Interpretation (Cat. No. 98EX165), pp. 256\u2013261 (1998)","DOI":"10.1109\/IAI.1998.666895"},{"issue":"4","key":"8_CR7","doi-asserted-by":"publisher","first-page":"635","DOI":"10.1142\/S0218001495000249","volume":"9","author":"I Debled-Rennesson","year":"1995","unstructured":"Debled-Rennesson, I., Reveill\u00e8s, J.: A linear algorithm for segmentation of digital curves. Int. J. Pattern Recognit. Artif. Intell. 9(4), 635\u2013662 (1995)","journal-title":"Int. J. Pattern Recognit. Artif. Intell."},{"key":"8_CR8","doi-asserted-by":"crossref","unstructured":"Decelle, R., Ngo, P., Debled-Rennesson, I., Mothe, F., Longuetaud, F.: Digital straight segment filter for geometric description. In: International Conference on Discrete Geometry and Mathematical Morphology, pp. 255\u2013268 (2021)","DOI":"10.1007\/978-3-030-76657-3_18"},{"key":"8_CR9","doi-asserted-by":"publisher","first-page":"558","DOI":"10.5201\/ipol.2022.338","volume":"12","author":"R Decelle","year":"2022","unstructured":"Decelle, R., Ngo, P., Debled-Rennesson, I., Mothe, F., Longuetaud, F.: Ant colony optimization for estimating pith position on images of tree log ends. Image Process. Line 12, 558\u2013581 (2022)","journal-title":"Image Process. Line"},{"key":"8_CR10","doi-asserted-by":"crossref","unstructured":"Decelle, R., Ngo, P., Debled-Rennesson, I., Mothe, F., Longuetaud, F.: Light u-net with a new morphological attention gate model application to analyse wood sections. In: ICPRAM 2023 (2023)","DOI":"10.5220\/0011626800003411"},{"key":"8_CR11","doi-asserted-by":"crossref","unstructured":"Decelle, R., Ngo, P., Debled-Rennesson, I., Mothe, F., Longuetaud, F.: Directional filter for tree ring detection. In: In Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods, pp. 852\u2013859 (2024)","DOI":"10.5220\/0012457000003654"},{"key":"8_CR12","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1016\/j.compag.2018.05.005","volume":"150","author":"A Fabija\u0144ska","year":"2018","unstructured":"Fabija\u0144ska, A., Danek, M.: Deepdendro-a tree rings detector based on a deep convolutional neural network. Comput. Electron. Agric. 150, 353\u2013363 (2018)","journal-title":"Comput. Electron. Agric."},{"key":"8_CR13","doi-asserted-by":"crossref","unstructured":"Gillert, A., Resente, G., Anadon-Rosell, A., Wilmking, M., von Lukas, U.F.: Iterative next boundary detection for instance segmentation of tree rings in microscopy images of shrub cross sections. In: Proceedings of IEEE CVFPR, pp. 14540\u201314548 (2023)","DOI":"10.1109\/CVPR52729.2023.01397"},{"key":"8_CR14","doi-asserted-by":"crossref","unstructured":"Gonzalez, R.C.: Digital Image Processing. Pearson Education India (2009)","DOI":"10.1117\/1.3115362"},{"key":"8_CR15","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of IEEE CCVPR, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"8_CR16","doi-asserted-by":"crossref","unstructured":"Jammalamadaka, S.R., Sengupta, A.: Topics in Circular Statistics, vol.\u00a05. world scientific (2001)","DOI":"10.1142\/9789812779267"},{"key":"8_CR17","doi-asserted-by":"crossref","unstructured":"Kirillov, A., et\u00a0al.: Segment anything. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4015\u20134026 (2023)","DOI":"10.1109\/ICCV51070.2023.00371"},{"issue":"1","key":"8_CR18","doi-asserted-by":"publisher","first-page":"192","DOI":"10.1109\/18.50392","volume":"36","author":"J Koplowitz","year":"1990","unstructured":"Koplowitz, J., Lindenbaum, M., Bruckstein, A.: The number of digital straight lines on an n* n grid. IEEE Trans. Info. Theory 36(1), 192\u2013197 (1990)","journal-title":"IEEE Trans. Info. Theory"},{"key":"8_CR19","doi-asserted-by":"crossref","unstructured":"Kurdthongmee, W.: A comparative study of the effectiveness of using popular DNN object detection algorithms for pith detection in cross-sectional images of parawood. Heliyon 6(2) (2020)","DOI":"10.1016\/j.heliyon.2020.e03480"},{"key":"8_CR20","unstructured":"Laggoune, H., Guesdon, V., et\u00a0al.: Tree ring analysis. In: IEEE Canadian Conference on Electrical and Computer Engineering, pp. 1574\u20131577 (2005)"},{"key":"8_CR21","doi-asserted-by":"crossref","unstructured":"Longuetaud, F., et\u00a0al.: Traceability and quality assessment of Douglas fir (pseudotsuga menziesii (Mirb.) franco) logs: the treetrace_douglas database. Annals Forest Sci. 79(1), 1\u201321 (2022)","DOI":"10.1186\/s13595-022-01163-7"},{"key":"8_CR22","unstructured":"Makela, K., Ophelders, T., Quigley, M., Munch, E., Chitwood, D., Dowtin, A.: Automatic tree ring detection using Jacobi sets. arXiv preprint arXiv:2010.08691 (2020)"},{"key":"8_CR23","unstructured":"Marichal, H., et al.: UruDendro: An Uruguayan Disk Wood Database For Image Processing (2023)"},{"key":"8_CR24","unstructured":"Marichal, H., Passarella, D., Randall, G.: CS-TRD: a cross sections tree ring detection method. arXiv preprint arXiv:2305.10809 (2023)"},{"issue":"2","key":"8_CR25","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1016\/j.compag.2008.02.006","volume":"63","author":"K Norell","year":"2008","unstructured":"Norell, K., Borgefors, G.: Estimation of pith position in untreated log ends in sawmill environments. Comput. Electron. Agric. 63(2), 155\u2013167 (2008)","journal-title":"Comput. Electron. Agric."},{"issue":"9","key":"8_CR26","doi-asserted-by":"publisher","first-page":"2233","DOI":"10.1111\/2041-210X.14183","volume":"14","author":"M Pol\u00e1\u010dek","year":"2023","unstructured":"Pol\u00e1\u010dek, M., Arizpe, A., H\u00fcther, P., Weidlich, L., Steindl, S., Swarts, K.: Automation of tree-ring detection and measurements using deep learning. Methods Ecol. Evol. 14(9), 2233\u20132242 (2023)","journal-title":"Methods Ecol. Evol."},{"key":"8_CR27","unstructured":"Reveill\u00e8s, J.P.: G\u00e9om\u00e9trie discrete, calcul en nombres entiers et algorithmique (1991)"},{"key":"8_CR28","unstructured":"RP 145: Rp 145:2004 - smpte recommended practice - smpte c color monitor colorimetry (2004). 10.5594\/SMPTE.RP145.2004"},{"issue":"3","key":"8_CR29","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","volume":"115","author":"O Russakovsky","year":"2015","unstructured":"Russakovsky, O., et al.: ImageNet large scale visual recognition challenge. Int. J. Comput. Vision 115(3), 211\u2013252 (2015). https:\/\/doi.org\/10.1007\/s11263-015-0816-y","journal-title":"Int. J. Comput. Vision"},{"key":"8_CR30","doi-asserted-by":"crossref","unstructured":"Venkatesh, M., Seelamantula, C.S.: Directional bilateral filters. In: Proceeding of IEEE ICASSP, pp. 1578\u20131582 (2015)","DOI":"10.1109\/ICASSP.2015.7178236"},{"key":"8_CR31","doi-asserted-by":"crossref","unstructured":"Wimmer, G., Schraml, R., Hofbauer, H., Petutschnigg, A., Uhl, A.: Two-stage CNN-based wood log recognition. In: International Conference on Computational Science and Its Applications, pp. 115\u2013125 (2021)","DOI":"10.1007\/978-3-030-87007-2_9"},{"key":"8_CR32","first-page":"12077","volume":"34","author":"E Xie","year":"2021","unstructured":"Xie, E., Wang, W., Yu, Z., Anandkumar, A., Alvarez, J.M., Luo, P.: SegFormer: simple and efficient design for semantic segmentation with transformers. Adv. Neural. Inf. Process. Syst. 34, 12077\u201312090 (2021)","journal-title":"Adv. Neural. Inf. Process. Syst."}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition Applications and Methods"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-06007-5_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T19:03:28Z","timestamp":1760900608000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-06007-5_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,20]]},"ISBN":["9783032060068","9783032060075"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-06007-5_8","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,20]]},"assertion":[{"value":"20 October 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPRAM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition Applications and Methods","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Rome","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 February 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 February 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icpram2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}