图像中目标测量的图聚类、变分图像分割方法和Hough变换尺度检测
Graph clustering, variational image segmentation methods and Hough transform scale detection for object measurement in images
摘要：
我们考虑图像中的尺度检测问题，其中感兴趣的区域与测量工具（例如，标尺）一起存在。对于分割部分，我们专注于基于图的方法Flenner和Bertozzi重新解释经典的连续Ginzburg-Landau最小化模型在一个完全离散的框架。为了克服由于考虑的图像的大尺寸的数值困难，我们使用矩阵完成和分裂技术。通过基于Hough变换的算法检测测量工具上的刻度。然后将该方法应用于实际应用中出现的一些测量任务，如动物学，医学和考古学。
英文摘要：
We consider the problem of scale detection in images where a region of interest is present together with a measurement tool (e.g. a ruler). For the segmentation part, we focus on the graph based method by Flenner and Bertozzi which reinterprets classical continuous Ginzburg-Landau minimisation models in a totally discrete framework. To overcome the numerical difficulties due to the large size of the images considered we use matrix completion and splitting techniques. The scale on the measurement tool is detected via a Hough transform based algorithm. The method is then applied to some measurement tasks arising in real-world applications such as zoology, medicine and archaeology.
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