Robust Object Detection in Colour Images Using a Multivariate Percentage Occupancy Hit-or-Miss Transform
Robust Object Detection in Colour Images Using a Multivariate Percentage Occupancy Hit-or-Miss Transform
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DOI：
10.1515/mathm-2020-0111
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发表时间：
2021-01
期刊：
影响因子：
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通讯作者：
Fraser Macfarlane;P. Murray;S. Marshall;B. Perret;A. Evans;Henry White
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文献类型：
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作者：
Fraser Macfarlane;P. Murray;S. Marshall;B. Perret;A. Evans;Henry White
摘要数学形态学扩展到彩色和多变量图像是具有挑战性的，由于需要定义一个总的颜色空间的顺序。没有一个通用的方法来排序多元数据存在，因此，没有一个单一的，明确的方式进行形态学操作的彩色图像。在本文中，我们提出了一个扩展的数学形态学，减少排序的基础上，特别是形态击中或错过变换，这是用于对象检测。所采用的减少的排序将多变量观察转换为标量比较，从而允许导出顺序并且允许使用平坦和非平坦结构元素。我们还比较了命中或失误变换和测试的其他定义的颜色排序方案在文献中提出的。我们提出的方法是直观的，优于其他方法的多元击中或错过变换。此外，建议击中或错过变换的参数设置的方法，以使变换鲁棒的噪声和部分遮挡的对象，最后，一组设计工具，以获得相应的设置这些参数的最佳值。
Abstract The extension of Mathematical Morphology to colour and multivariate images is challenging due to the need to define a total ordering in the colour space. No one general way of ordering multivariate data exists and, therefore, there is no single, definitive way of performing morphological operations on colour images. In this paper, we propose an extension to mathematical morphology, based on reduced ordering, specifically the morphological Hit-or-Miss Transform which is used for object detection. The reduced ordering employed transforms multivariate observations to scalar comparisons allowing for an order to be derived and for both flat and non-flat structuring elements to be used. We also compare other definitions of the Hit-or-Miss Transform and test alternative colour ordering schemes presented in the literature. Our proposed method is shown to be intuitive and outperforms other approaches to multivariate Hit-or-Miss Transforms. Furthermore, methods of setting the parameters of the proposed Hit-or-Miss Transform are introduced in order to make the transform robust to noise and partial occlusion of objects and, finally, a set of design tools are presented in order to obtain optimal values for setting these parameters accordingly.