DocumentCode :
2520442
Title :
Fast retrieval on compressed images for internet applications
Author :
Albanesi, Maria Grazia ; Giacane, A.
Author_Institution :
Dipt. di Inf. e Sistemistica, Pavia Univ., Italy
fYear :
2000
fDate :
2000
Firstpage :
136
Lastpage :
141
Abstract :
In this paper we present a method to incorporate a content-based retrieval algorithm on compressed images with a digital image transform scheme to achieve a low cost and fast indexing method. The target application is the access and interaction with huge amount of visual data on Internet. The approach exploits a modified Wavelet multiresolution decomposition and reconstruction scheme and a multiresolution algorithm for feature extraction and index generation. The efficacy of the method has been proved by extensive tests on YUV compressed JPEG images and the performance have been compared with other approaches on uncompressed, original images, even with the addition of noise. The results suggest a great opportunity to embed in a unique paradigm a fast retrieval technique and a good compression algorithm of low computational complexity, very suitable for Internet imaging applications
Keywords :
Internet; computational complexity; content-based retrieval; data compression; database indexing; feature extraction; image coding; Internet; Internet imaging; YUV compressed JPEG images; compressed images retrieval; computational complexity; content-based retrieval algorithm; digital image transform scheme; feature extraction; index generation; indexing; modified Wavelet multiresolution decomposition; multiresolution algorithm; performance; visual data; Content based retrieval; Costs; Digital images; Feature extraction; Image coding; Image reconstruction; Image retrieval; Indexing; Internet; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Architectures for Machine Perception, 2000. Proceedings. Fifth IEEE International Workshop on
Conference_Location :
Padova
Print_ISBN :
0-7695-0740-9
Type :
conf
DOI :
10.1109/CAMP.2000.875970
Filename :
875970
Link To Document :
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