TY - GEN
T1 - Digital image similarity for geo-spatial knowledge management
AU - Carswell, James D.
AU - Wilson, David C.
AU - Bertolotto, Michela
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2002.
PY - 2002
Y1 - 2002
N2 - The amount and availability of high-quality geo-spatial image data, such as digital satellite and aerial photographs, is increasing dramatically. Task-based management of such visual information and associated knowledge is a central concern for organisations that rely on digital imagery. We are developing geo-spatial knowledge management techniques that employ case-based reasoning as the core methodology. In order to provide effective retrieval of task-based experiences that center around geo-spatial imagery, we need to forward novel similarity metrics for directly comparing the image components of experience cases. Based on work in geo-spatial image database retrieval, we are building an effective similarity metric for geo-spatial imagery that makes comparisons based on derived image features, their shapes, and the spatial relations between them. This paper gives an overview of the geo-spatial knowledge management context, describes our image similarity metric, and provides an initial evaluation of the work.
AB - The amount and availability of high-quality geo-spatial image data, such as digital satellite and aerial photographs, is increasing dramatically. Task-based management of such visual information and associated knowledge is a central concern for organisations that rely on digital imagery. We are developing geo-spatial knowledge management techniques that employ case-based reasoning as the core methodology. In order to provide effective retrieval of task-based experiences that center around geo-spatial imagery, we need to forward novel similarity metrics for directly comparing the image components of experience cases. Based on work in geo-spatial image database retrieval, we are building an effective similarity metric for geo-spatial imagery that makes comparisons based on derived image features, their shapes, and the spatial relations between them. This paper gives an overview of the geo-spatial knowledge management context, describes our image similarity metric, and provides an initial evaluation of the work.
UR - https://www.scopus.com/pages/publications/84942778103
U2 - 10.1007/3-540-46119-1_6
DO - 10.1007/3-540-46119-1_6
M3 - Conference contribution
AN - SCOPUS:84942778103
SN - 3540441093
SN - 9783540441090
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 58
EP - 72
BT - Advances in Case-Based Reasoning - 6th European Conference, ECCBR 2002, Proceedings
A2 - Craw, Susan
A2 - Preece, Alun
PB - Springer Verlag
T2 - 6th European Conference on Case-Based Reasoning, ECCBR 2002
Y2 - 4 September 2002 through 7 September 2002
ER -