为什么在感知哈希中创建哈希?

I've been working through the examples at http://www.hackerfactor.com/blog/index.php?/archives/432-Looks-Like-It.html&comment-submitted#feedback and I got stuck trying to create a hash from the bits of the image after it's processed. If you hash the binary string created from the pixels of an image and then look at the hamming distance to analyze how different the photos are, what good is creating a hash doing a hamming distance vs. doing a hamming distance on the raw binary string? Is the hash created merely to speed things up?

我对哈希不太了解。我假设在这种情况下,它们可以作为几乎相同照片的过滤机制?但这种过滤不是通过缩小照片并将其转换为灰度来实现的吗?

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1 答案

博客文章中提出的想法是如何识别类似的图片。目标是丢失正确的信息,以便留下重要且易于比较的信息。因此有两个方面:您可以比较多快和多准确。如果你将你的图片缩小到8x8黑白(即64位信息),那么你把它称为“原始咬合字符串”或“长字符串”并不重要(好吧,正如@Blender所说的那样)它并不是传统使用术语中的哈希值。重要的是如何减少它,剩下什么信息和丢失的东西。

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