Browsing, searching, and retrieving images has never been easy. Traditionally, many technologies relied on manually appending metadata to images and searching via this metadata. This approach works for datasets with high-quality annotation, but most datasets are too large for manual annotation.
That means any large image dataset must rely on Content-Based Image Retrieval (CBIR). Search with CBIR focuses on comparing the content of an image rather than its metadata. Content can be color, shapes, textures – or with some of the latest advances in ML — the “human meaning” behind an image.
This is a companion discussion topic for the original entry at https://www.pinecone.io/learn/color-histograms/