Open AccessBag‐of‐binary‐features for fast image representation
Author(s) -
Lee Suwon,
Choi SuGil,
Yang Hyun S.
Publication year - 2015
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2015.0080
Subject(s) - binary number , representation (politics) , binary image , image (mathematics) , pattern recognition (psychology) , set (abstract data type) , feature (linguistics) , feature extraction , artificial intelligence , computer science , yield (engineering) , image processing , mathematics , materials science , linguistics , philosophy , arithmetic , politics , political science , law , programming language , metallurgy
The possibility of integrating binary features into the bag‐of‐features (BoFs) model is explored. The set of binary features extracted from an image are packed into a single vector form, to yield the bag‐of‐binary‐features (BoBFs). The efficient BoBF feature extraction and quantisation provide fast image representation. The trade‐off between accuracy and efficiency in BoBF compared with BoF is investigated through image retrieval tasks. Experimental results demonstrate that BoBF is a competitive alternative to BoF when the run‐time efficiency is critical.