Abstract
A model-based method for training feedforward, backpropagation neural-like networks to produce edge images from data such as forward looking infrared and gray tone pictures is presented. The authors' approach is to train the network on a very small basis set of binary-valued window vectors which are first scored using the Sobel edge operator. Sobel scores are then used to select training vectors that have either crisp or fuzzy edge labels. This training scheme is independent of all real images. The method proposed is illustrated by comparing FF/BP edge images with those produced by the Sobel and Canny edge operators. >
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
