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Image Indexing and Retrieval Methods: Manual, Visual Similarity, and Keywords in HTML

Understand the workings of each system for indexing and retrieving images - manual indexing, visual similarity (QBIC/Blobworld), and the use of keywords in HTML. Examine the strengths and weaknesses of each approach and the types of queries they are suitable for.

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Image Indexing and Retrieval Methods: Manual, Visual Similarity, and Keywords in HTML

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  1. What do you understand about how each system works to index-retrieve images? Manually Index Expensive but effective

  2. What do you understand about how each system works to index-retrieve images? Visual Similarity (QBIC / Blobworld) User makes a visual query (i.e. “I want image(s) that look like this”) – where “look like” is defined mathematically by the system (e.g. colour histograms, texture, shape)

  3. What do you understand about how each system works to index-retrieve images? Use keywords in HTML (search engines) ?How to select the keywords? Take from the filename / directory names Take them from the ALT tag ??Maybe take them from the rest of the text on the webpage??

  4. What do you think are the strengths and weaknesses of each approach / system? What kinds of information needs / queries are they good for? Manual indexing – good when there’s a business model Visual Similarity – match patterns like trademarks, find a painting whose name you’ve forgotten, find images to match a colour schemes Keywords in HTML – best we’ve got for general web searches

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