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Digital image

As explained in AI-Powered Search

An image is visual data represented as a grid of colors that forms a picture.

A digital image is unstructured visual data represented as a grid of colors that forms a picture. Search systems handle images alongside text, audio, and video. section 2.1.1

Image search can represent and retrieve images in two main ways:

  • Search an inverted index using text descriptions or labels attached to images. section 15.3.1
  • Encode images as embedding vectors, index those vectors, and encode a query image to retrieve visually or conceptually similar images. section 15.3.1

From picture to search result

A stored image can carry a text label for inverted-index search. Alternatively, a vision Transformer can convert the stored image and a new query image into embedding vectors, allowing the system to rank visually similar images. section 15.3.1

Figure 2.2 Multiple types of unstructured data. In addition to the text from the last figure, we now see images, audio, and video, which are other forms of unstructured data.
figure

Use the figure to compare images with other unstructured data types, including text, audio, and video. section 2.1.1

How AI-Powered Search covers it

How deep it goes
Defines images as color grids and outlines label-based and vector-based retrieval, stopping short of embedding-model training details.
Examples
Uses color grids, image labels, text descriptions, stored images, and query images as concrete artifacts.
What you can do after
Understand image retrieval through labels or embedding vectors and distinguish visual similarity search from text-based indexing.
How it connects
Connects images to unstructured data, multimodal search, inverted indexes, embedding vectors, and vision Transformers.

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Related concepts

This explainer was generated by Manning's knowledge graph from the text of AI-Powered Search. The section links point to the parts of the book it draws on.