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Understanding leaves in natural images - A model-based approach for tree species identification

机译:了解自然图像中的叶子-一种基于模型的树木物种识别方法

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With the aim of elaborating a mobile application, accessible to anyone and with educational purposes, we present a method for tree species identification that relies on dedicated algorithms and explicit botany-inspired descriptors. Focusing on the analysis of leaves, we developed a working process to help recognize species, starting from a picture of a leaf in a complex natural background. A two-step active contour segmentation algorithm based on a polygonal leaf model processes the image to retrieve the contour of the leaf. Features we use afterwards are high-level geometrical descriptors that make a semantic interpretation possible, and prove to achieve better performance than more generic and statistical shape descriptors alone. We present the results, both in terms of segmentation and classification, considering a database of 50 European broad-leaved tree species, and an implementation of the system is available in the iPhone application Folia.
机译:为了开发一种移动应用程序,任何人都可以访问并出于教育目的,我们提出了一种树种识别方法,该方法依赖于专用算法和受植物学启发的描述符。我们着重于叶片的分析,从复杂自然背景下的叶片图片开始,我们开发了一种有助于识别物种的工作流程。基于多边形叶模型的两步主动轮廓分割算法对图像进行处理以检索叶的轮廓。我们随后使用的功能是高级几何描述符,这些描述符使语义解释成为可能,并且比单独使用更通用和统计形状的描述符证明具有更好的性能。考虑到欧洲50种阔叶树种的数据库,我们在分割和分类方面都给出了结果,并且该系统的实现在iPhone应用程序Folia中可用。

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