Paper Info
Title
Singular value decomposition image compression system for automatic object recognition
Abstract
In this paper we present a lossy approach to compress digital images, in which the decompressed images have the sufficient quality to be used for Computer Vision (CV) tasks as pattern recognition. To compress the images we use the Singular Value Decomposition (SVD) transform, which allow to refactoring a digital image in three matrices. The use of the resulting singular values of such refactoring allows us to represent the image with a smaller set of values and achieve the lossy image compression process. This compression method preserves useful features of the original image to perform automatic object recognition (AOR) over the decompressed image using software of National Instruments called "Vision Builder". Additionally we show the preliminary results of the constructed system for compression/decompression and for the AOR.
Year
Venue
Keywords
2006
ACST
lossy image compression process,singular value decomposition image,vision builder,compression system,lossy approach,compression method,digital image,decompressed image,automatic object recognition,compress digital image,computer vision,original image,image compression,pattern recognition,singular value decomposition,object recognition
Field
DocType
ISBN
Computer vision,Singular value decomposition,Singular value,3D single-object recognition,Lossy compression,Pattern recognition,Computer science,Digital image,Software,Artificial intelligence,Code refactoring,Image compression
Conference
0-88986-545-0
Citations 
PageRank 
References 
2
0.36
2
Authors
3
Name
Order
Citations
PageRank
Osslan Osiris Vergara Villegas1156.40
Raul Pinto Elias251.13
Vianey Guadalupe Cruz Sánchez3277.24