Abstract: The invention is an optical-digital method and processor which uses micro-optical lenslet arrays and fixed masks to implement an angular correlation algorithm and the Hough transform for extracting amplitude and geometric features from objects embedded in video imagery. The optical-digital processor can be interfaced to a variety of sensors and can be used to classify objects when used in conjunction with a neural network.

Abstract: A method and electro-optical apparatus for generating the Radon transform and angular correlation of input images using optical signal processing techniques is disclosed. In the preferred embodiment, video feedback of raster scanned images is utilized to perform the Radon transform and angular correlation separately or in combination. The basic video feedback architecture implements angular rotation of the input image via successive passes through a video feedback loop in which the feedback focal plane array is rotated by a fixed amount relative to the input/feedback miniature display unit. Subsequently, the Radon transform is derived by using anamorphic output optics, which image the Radon transform onto a linear self-scanned detector array.