Mastering Computer Vision with TensorFlow 2.x

Detecting edges using image hashing and filtering

Image hashing is a method used to find similarity between images. Hashing involves modifying an input image to a fixed size of binary vector through transformation. There are different algorithms for image hashing using different transformations:

• Perpetual hash (phash): A cosine transformation
• Difference hash (dhash): The difference between adjacent pixels

After a hash transformation, images can be compared quickly with the Hamming distance. The Python code for applying a hash transformation is shown in the following code. A hamming distance of 0 shows an identical image (duplicate), whereas a larger hamming distance shows that the images are different from each other. The following snippet ...