TECHNIQUE FOR OBJECT ORIENTATION DETECTION USING A FEED-FORWARD NEURAL NETWORK

摘要

The present invention relates to a technique in the form of an exemplary computer vision system for detecting the orientation of text or features on an object of manufacture. In the present system, an image of the features or text (10) is used to extract lines using horizontal bitmap sums, and then individual symbols (12) using vertical bitmap sums while using thresholds with each of the sums. The separated symbols are then appropriately trimmed and scaled to provide individual normalized symbols (14). A Decision Module (15) comprising a Feed-Forward Neural network (21) and a sequential decision arrangement (23) determines the "up", "down" or "indeterminate" orientation of the text after a variable number of symbols have been processed. The system can then compare (24) the determined orientation with a database to further determine if the object is in the "right-side up" "upside-down" or "indeterminate" orientation.