How to use Color Histograms for Image Retrieval
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.

Color histograms represent one of the first CBIR techniques, allowing us to search through images based on their color profiles rather than metadata.

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00:00 Intro
01:23 What are Color Histograms?
08:39 How to Built Color Histograms
16:56 Using OpenCV calcHist
20:36 Image Retrieval
27:37 Pros and Cons
30:40 Final Points