| 摘要 |
<p>Architecture that automatically computes if a quadrangular object captured in a given image is or is not a markable board (e.g., a whiteboard, green board, chalkboard, etc.). The markable board has a surface on which marks can be applied using chalk, ink, dry ink, or any other suitable marking instrument or tool for the given surface. The imaged quadrangular object can be defined as having a background image and a foreground image. The background image is representative of a markable board with no applied surface marks and the foreground image comprises all discernible marks applied to the board surface, but does not include the background image. A set of performance- friendly features is received and processed by a machine-learning classifier to compute if the given quadrangular object is a markable board. Thereafter, if the given image is determined to be a markable board, image enhancement is performed.</p> |
