Title :
Storage and retrieval of compressed images
Author :
Idris, F. ; Panchanathan, S.
Author_Institution :
Dept. of Electr. Eng., Ottawa Univ., Ont., Canada
fDate :
8/1/1995 12:00:00 AM
Abstract :
In this paper, we propose a new technique for the storage and retrieval of compressed images. Here, the images are compressed using vector quantization and the codebook is used to generate a feature vector. This feature vector is used as an index to access the images in the database. This technique combines image compression with image indexing. In addition, it has lower storage and computation requirements compared with other techniques reported in the literature
Keywords :
computational complexity; data compression; image coding; vector quantisation; video coding; visual databases; codebook; compressed images; computation requirements; database; feature vector; image indexing; image retrieval; image storage; vector quantization; Clustering algorithms; Histograms; Image coding; Image databases; Image retrieval; Image storage; Indexing; Iterative algorithms; Spatial databases; Vector quantization;
Journal_Title :
Consumer Electronics, IEEE Transactions on
