Generally speaking, some simple expression of the performance of image search engines is desirable.
In information retrieval theory, precision is the percentage of relevant documents retrieved compared to the number of all the documents retrieved, and recall is the percentage of relevant documents retrieved out of all relevant documents. Recall and precision are widely used for reporting retrieval performance for image retrieval systems as well. However, these measures are affected by the database size and the amount of similar information in the database. Also, they do not consider fuzzy matching or search result ordering.
In equation form, these quantities are defined as
In general, the more we relax threesholds and allow more images to be returned, the smaller the precision, but the larger the recall. The curve of precision versus recall is termed a receiver operator characteristic (ROC) curve. It plots the relationship between sensitivity and specificity over a range of parameters.
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Introduction To Multimedia
Multimedia Authoring And Tools
Graphics And Image Data Representations
Colour In Image And Video
Fundamental Concepts In Video
Basics Of Digital Audio
Lossless Compression Algorithm
Lossy Compression Algorithms
Image Compression Standards
Basic Video Compression Techniques
Mpeg Video Coding I – Mpeg 1 And 2
Mpeg Video Coding Ii- Mpeg-4, 7, And Beyon
Basic Audio Compression Techniques
Mpeg Audio Compression
Computer And Multimedia Networks
Multimedia Network Communications And Applications
Content-based Retrieval In Digital Libraries
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