Perceptual Hashing

One of the best ways to track down duplicates of a copyright image is by using perceptual hashes — and to do that, you need to create these hashes in the first place. Using the complementary Python code below, you can easily take advantage of a perceptual hash generation API…

The purpose of generating a perceptual hash is to facilitate a comparison between one image and any copies or altered versions of that image which may exist on the web without our knowledge (the similarity between such images based on a perceptual hash is referred to as a Hamming Distance)…

Sometimes referred to as “digital fingerprinting,” perceptual hashing is a ubiquitous & highly effective way of tracking duplicate versions of original media content across the web. …

Learn how to use perceptual hash functions and nearest neighbor searches to detect duplicate images — Table of Contents Motivation Implementation Details Building the System Testing Future Improvements References Motivation You might be wondering, “what’s the point of making a duplicate image detection system?”, well there are a few reasons why you might want to. These reasons include preventing copyright infringement to removing illegal or unwanted images from a web…

Image searching is a type of information retrieval method in which similar images are retrieved based on the query which is also an image. Image searching is widely used in Forensics, Surveillance, etc. Every modern browser provides an image searching feature to retrieve websites that have similar images asked in…

Did you ever find yourself in a situation where you had a directory full of images and might have potential duplicates? To look through each image and mark duplicates will be a waste of your time, and so, you wanted to automate it with a script. …

At OkCupid, we sometimes run into users and bots that re-use the same photos we’ve seen before. While sometimes we can simply check if a photo has been seen (and banned) before, we often run into the case where a banned photo has been manipulated slightly — so an exact…