Browse Bar: Browse by Author | Browse by Category | Browse by Citation | Advanced Search
CONFIGR-STARS applies CONFIGR (CONtour FIgure and GRound) to solve the problem of star image registration. CONFIGR (CONtour FIgure and GRound) is a computational model based on principles of biological vision that completes sparse and noisy image figures. Star signatures based on CONFIGR connections uniquely identify a location in the sky, with the geometry of each signature encoding and locating unknown test images.
Arun Ravindran
CONFIGR-STARS, a new methodology based on a model of the human visual system, is developed for registration of star images. The algorithm first applies CONFIGR, a neural model that connects sparse and noisy image components. CONFIGR produces a web of connections between stars in a reference starmap or in a test patch of unknown location. CONFIGR-STARS splits the resulting, typically highly connected, web into clusters, or “constellations.” Cluster geometry is encoded as a signature vector that records edge lengths and angles relative to the cluster’s baseline edge. The location of a test patch cluster is identified by comparing its signature to signatures in the codebook of a reference starmap, where cluster locations are known. Simulations demonstrate robust performance in spite of image perturbations and omissions, and across starmaps from different sources and seasons. Further studies would test CONFIGR-STARS and algorithm variations applied to very large starmaps.
3 files are included in the compressed software package:
configr_stars_train.m -- to generate star signatures for the starmap.
configr_stars_test.m -- to locate an unknown patch.
configr_stars_extract_nodes_edges.m -- to extract signatures from CONFIGR conenctions.
NOTE: Please refer to CONFIGR software (http://techlab.bu.edu/resources/software_view/configr_contour_figure_ground/) on how to run CONFIGR
OS independent
Matlab
Retail software
Gail Carpenter
