TY - GEN
T1 - An efficient method of constructing L1-type norm feature to estimate euclidean distance for fast vector quantization
AU - Pan, Zhibin
AU - Kotani, Koji
AU - Ohmi, Tadahiro
PY - 2004
Y1 - 2004
N2 - In order to speed up the search process of vector quantization (VQ), it is most important to avoid computing k-dimensional Euclidean distance as many as possible. In order to find a best-matched codeword (winner) in the codebook for a certain input vector, it is a general way to roughly estimate other than exactly compute Euclidean distance immediately for the purpose of rejecting a candidate codeword. The lower dimensional features of a vector such as sum or the mean (L1 norm) and L2 norm are widely used for this purpose. Obviously, how to construct a suitable feature is a core problem for estimating Euclidean distance. In this paper, an efficient method of constructing L1-type norm feature is proposed by introducing a reference vector. In addition, the criterion on how to select an optimal reference vector is also given. Experimental results confirmed the effectiveness of the proposed method.
AB - In order to speed up the search process of vector quantization (VQ), it is most important to avoid computing k-dimensional Euclidean distance as many as possible. In order to find a best-matched codeword (winner) in the codebook for a certain input vector, it is a general way to roughly estimate other than exactly compute Euclidean distance immediately for the purpose of rejecting a candidate codeword. The lower dimensional features of a vector such as sum or the mean (L1 norm) and L2 norm are widely used for this purpose. Obviously, how to construct a suitable feature is a core problem for estimating Euclidean distance. In this paper, an efficient method of constructing L1-type norm feature is proposed by introducing a reference vector. In addition, the criterion on how to select an optimal reference vector is also given. Experimental results confirmed the effectiveness of the proposed method.
KW - Euclidean distance
KW - Fast vector quantization
KW - L-type norm feature
UR - http://www.scopus.com/inward/record.url?scp=32844470874&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=32844470874&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:32844470874
SN - 188933524X
T3 - Image Processing, Biomedicine, Multimedia, Financial Engineering and Manufacturing - Proceedings of the Sixth Biannual World Automation Congress
SP - 217
EP - 222
BT - Image Processing, Biomedicine, Multimedia, Financial Engineering and Manufacturing - International Forum on Multimedia Image Processing, IFMIP - Proceedings of the Sixth Biannual World Automation Cong
A2 - Jamshidi, M.
A2 - Hata, Y.
A2 - Kamrani, A.
A2 - Jamshidi, J.S.
T2 - Image Processing, Biomedicine, Multimedia, Financial Engineering and Manufacturing - International Forum on Multimedia Image Processing, IFMIP - Sixth Biannual World Automation Congress, WAC 2004
Y2 - 26 June 2004 through 1 July 2004
ER -