We discuss and present preliminary results about an algorithm which is trained to locate objects in images. The algorithm determines the parameters for a generalized Hough transform based on training images. Our training images consist of binary edge images from noisy imagery and identified points and boundaries for the objects being located in this imagery. The resulting generalized Hough transform will find objects of the same type at a wide variety of scales and any orientation present in the training data.
David B. Sher,
Elyse H. Podnos,
"Generating object locators from a training ensemble", Proc. SPIE 1962, Adaptive and Learning Systems II, (1 September 1993); doi: 10.1117/12.150583; https://doi.org/10.1117/12.150583