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SmartWoodID-一个大型横截面表面图像集合,用于支持木材识别系统。

SmartWoodID-an image collection of large end-grain surfaces to support wood identification systems.

机构信息

Service of Wood Biology, Royal Museum for Central Africa, Leuvensesteenweg 13, Tervuren 3080, Belgium.

Jodrell laboratory, Royal Botanic Gardens, Kew, Richmond, London TW9 3A, UK.

出版信息

Database (Oxford). 2023 May 13;2023. doi: 10.1093/database/baad034.

Abstract

Wood identification is a key step in the enforcement of laws and regulations aimed at combatting illegal timber trade. Robust wood identification tools, capable of distinguishing a large number of timbers, depend on a solid database of reference material. Reference material for wood identification is typically curated in botanical collections dedicated to wood consisting of samples of secondary xylem of lignified plants. Specimens from the Tervuren Wood Collection, one of the large institutional wood collections around the world, are used as a source of tree species data with potential application as timber. Here, we present SmartWoodID, a database of high-resolution optical scans of the end-grain surfaces enriched with expert wood anatomical descriptions of macroscopic features. These can serve as annotated training data to develop interactive identification keys and artificial intelligence for computer vision-based wood identification. The first edition of the database consists of images of 1190 taxa, with a focus on potential timber species from the Democratic Republic of the Congo with at least four different specimens per species included. Database URL https://hdl.handle.net/20.500.12624/SmartWoodID_first_edition.

摘要

木材鉴定是打击非法木材贸易法规执行的关键步骤。能够鉴别大量木材的可靠木材鉴定工具,依赖于参考资料的坚实数据库。木材鉴定的参考资料通常由专门的木材植物学收藏库维护,其中包括木质化植物次生木质部的样本。特文伦木材收藏(Tervuren Wood Collection)是世界上大型机构木材收藏之一,其标本被用作具有潜在木材应用价值的树种数据来源。在这里,我们介绍 SmartWoodID,这是一个具有专家木材解剖宏观特征描述的高分辨率末端表面光学扫描的数据库。这些可以作为带注释的训练数据,用于开发交互式识别钥匙和基于计算机视觉的人工智能木材识别。该数据库的第一版包含 1190 个分类群的图像,重点是来自刚果民主共和国的潜在木材物种,每个物种至少包含四个不同的样本。数据库网址:https://hdl.handle.net/20.500.12624/SmartWoodID_first_edition。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b152/10182821/1d9807665771/baad034f1.jpg

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