Abstract: Entropy based image segmentation determines entropy values for pixels in an image based on intensity or edge orientation. One or more threshold values are determined as a fraction of the entropy distribution over the image. For example, high and/or low thresholds may be generated to identify regions in the image associated with trees or sky, respectively. The entropy values are compared to the threshold(s) from which regions within the image can be segmented. Intensity based entropy has no structural information, and thus, proximity based clustering and pruning of the entropy points is performed. A mask may be applied to the segmented regions to remove the regions from the image, which is useful in, e.g., objection recognition processes. Additionally, separate buildings may be identified and segmented using edge orientation entropy with clustering and pruning.

Abstract: Disclosed is an apparatus for providing remote testing and monitoring of equipment backup batteries at the location of the batteries. The testing can be accomplished upon command from a remote terminal or remote agent as well as in accordance with predetermined parameters programmed into a processor at the remote site. The test is accomplished using the normal site load while reducing the amplitude of the DC (direct current) output voltage, obtained from an AC (alternating current) rectifier used at the site, from a battery charging “float” level amplitude during the duration of the test. The discharge curve obtained during the test is compared with previous and/or standardized curves to ascertain the condition of the battery tested and/or the likelihood of near future failure of the battery tested.