Data Management and Internet Computing for Image/Pattern Analysis
focuses on the data management issues and Internet computing aspect of
image processing and pattern recognition research. The book presents a
comprehensive overview of the state of the art, providing detailed case
studies that emphasize how image and pattern (IAP) data are distributed
and exchanged on sequential and parallel machines, and how the data
communication patterns in low- and higher-level IAP computing differ
from general numerical computation, what problems they cause and what
opportunities they provide. The studies also describe how the images and
matrices should be stored, accessed and distributed on different types
of machines connected to the Internet, and how Internet resource sharing
and data transmission change traditional IAP computing.
Data Management and Internet Computing for Image/Pattern Analysis is
divided into three parts: the first part describes several software
approaches to IAP computing, citing several representative data
communication patterns and related algorithms; the second part
introduces hardware and Internet resource sharing in which a wide range
of computer architectures are described and memory management issues are
discussed; and the third part presents applications ranging from image
coding, restoration and progressive transmission.
Data Management and Internet Computing for Image/Pattern Analysis is
an excellent reference for researchers and may be used as a text for
advanced courses in image processing and pattern recognition.