Abstract: Disclosed is a method and apparatus for detecting and ranging cloud features. The method comprises: obtaining image data (e.g. using a camera (200); classifying, as a cloud feature, an image segment (502-508) of the image data; determining a plurality of moments of the image segment (502-508); using the determined plurality of moments, determining a geometric representation of that image segment (502-508); and, using the geometric representation, determining a distance between the cloud feature represented by that image segment (502-508) and an entity that obtained the image data.

Abstract: Described herein are a system and method for identifying extremities of an object within a scene. The method comprises operating an image processing system to receive image data from a sensor. The image data represents an image of the scene with the object. The image data comprises a two-dimensional array of pixels and each pixel contains a depth value indicating distance from the sensor. The image processing system slices the image into slices. Each respective slice comprises those pixels with depth values that lie within a respective range of distances defined relative to a reference. For each of the slices, the method identifies one or more connected regions of pixels that are neighbors in the two-dimensional array of pixels. The method builds, based on the connected region of pixels that have been identified for the slices and depth information inherent to the respective slices, a graph consisting of interconnected nodes.

Abstract: Multiple modality contrast can be used to produce images that can be combined and rendered to produce images similar to those produced with wavelength absorbing stains viewed under transmitted white light illumination. Images obtained with other complementary contrast modalities can be presented using engineered color schemes based on classical contrast methods used to reveal the same anatomical structures and histochemistry, thereby providing relevance to medical training and experience. Dark-field contrast images derived from refractive index and fluorescent DAPI counterstain images are combined to produce images similar to those obtained with conventional H&E staining for pathology interpretation.