Efficiency issues related to probability density function comparison | Zendy

Patrick Kelly | Zendy; T. M. Can | Zendy; Julio E. Barros | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

<title>Efficiency issues related to probability density function comparison</title>

Author(s) -

Patrick Kelly,

T. M. Can,

Julio E. Barros

Publication year - 1996

Publication title -

proceedings of spie, the international society for optical engineering/proceedings of spie

Language(s) - English

Resource type - Conference proceedings

SCImago Journal Rank - 0.192

H-Index - 176

eISSN - 1996-756X

pISSN - 0277-786X

DOI - 10.1117/12.234808

Subject(s) - probability density function , computer science , gaussian , speedup , feature vector , representation (politics) , computation , gaussian function , feature (linguistics) , algorithm , function (biology) , probability distribution , measure (data warehouse) , similarity (geometry) , pattern recognition (psychology) , image (mathematics) , artificial intelligence , data mining , mathematics , statistics , linguistics , physics , philosophy , quantum mechanics , evolutionary biology , politics , biology , political science , law , operating system

The CANDID project (Comparison Algorithm for Navigating Digital Image Databases) employs probabilitydensity functions (PDFs) of localized feature information to represent the content of an image for search andretrieval purposes. A similarity measure between PDFs is used to identify database images that are similar toa user-provided query image. Unfortunately, signature comparison involving PDFs is a very time-consumingoperation. In this paper, we look into some efficiency considerations...

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research