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Real Two Dimensional Scaled Matching

机译:实数二维比例匹配

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摘要

Scaled Matching refers to the problem of finding all locations in the text where the pattern, proportionally enlarged according to an arbitrary real-sized scale, appears. Scaled matching is an important problem that was originally inspired by Computer Vision.rnFinding a combinatorial definition that captures the concept of real scaling in discrete images has been a challenge in the pattern matching field. No definition existed that captured the concept of real scaling in discrete images, without assuming an underlying continuous signal, as done in the image processing field. We present a combinatorial definition for real scaled matching that scales images in a pleasing natural manner. We also present efficient algorithms for real scaled matching.rnThe running times of our algorithms are as follows. For T, a two-dimensional n × n text array, and P, an m × m pattern array, we find in T all occurrences of P scaled to any real value in time O(nm~3 + n~2m logm).
机译:缩放匹配是指在文本中查找出现根据任意实际尺寸比例按比例放大的图案的所有位置的问题。缩放匹配是一个最初受到Computer Vision启发的重要问题。在模式匹配领域中,找到一个可以捕获离散图像中实际缩放概念的组合定义一直是一个挑战。在图像处理领域中,没有一种假设可以在不假设基础连续信号的情况下捕获离散图像中实际缩放的概念。我们提出了一个真实的比例匹配的组合定义,该定义以令人愉悦的自然方式缩放图像。我们还提出了用于实际比例匹配的有效算法。rn我们的算法的运行时间如下。对于T(一个二维n×n文本数组)和P(一个m×m模式数组),我们在T中发现所有出现的P都在时间O(nm〜3 + n〜2m logm)缩放为任何实际值。

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