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Object Descriptors Based on a List of Rectangles: Method and Algorithm

机译:基于矩形列表的对象描述符:方法和算法

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Most morphological operators use a unique structuring element, possibly at different scales, to describe an object. In addition, morphological algorithms are often restricted to ID structuring elements, combinations of ID elements, or isotropic structuring elements (like circles), because of the lack of methods directly applicable to arbitrary shaped 2D structuring elements. While these descriptors have proved useful in the past, we propose an alternative that uses the list of maximal rectangles contained in a set X.In particular, we focus on an opening that preserves large rectangles contained in a set X and on its companion 2D algorithm that builds a list of all the maximal rectangles that fit inside an arbitrary set X. This list is the base of new descriptors that have been used successfully for machine learning tasks related to the analysis of human silhouettes. For convenience, we provide the C source code and a program of our algorithm at http://www.ulg.ac.be/telecom/rectamgles
机译:大多数形态算子使用独特的结构元素(可能以不同的比例)来描述对象。另外,由于缺乏直接适用于任意形状的2D结构元素的方法,形态学算法通常仅限于ID结构元素,ID元素的组合或各向同性结构元素(如圆形)。尽管这些描述符在过去被证明是有用的,但我们提出了一个替代方案,该替代方案使用集合X中包含的最大矩形的列表,特别是,我们着眼于保留集合X中包含的大矩形的开口及其配套的2D算法会建立一个适合于任意集合X的所有最大矩形的列表。此列表是新描述符的基础,这些描述符已成功用于与人体轮廓分析相关的机器学习任务。为了方便起见,我们在http://www.ulg.ac.be/telecom/rectamgles提供了C源代码和算法程序。

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