Technique for object orientation detection using a feed-forward neural network
Patent 5060276 Issued on October 22, 1991. Estimated Expiration Date: 
May 31, 2009. Estimated Expiration Date is calculated based on simple USPTO term provisions. It does not account for terminal disclaimers, term adjustments, failure to pay maintenance fees, or other factors which might affect the term of a patent.
May 31, 2009. Estimated Expiration Date is calculated based on simple USPTO term provisions. It does not account for terminal disclaimers, term adjustments, failure to pay maintenance fees, or other factors which might affect the term of a patent.Patent References 3801775 3847346 Method of and video system for identifying different light-reflective surface areas on articles Printed circuit board defect detection of detecting maximum line width violations Distribution installation for moving piece goods System for printed circuit board defect detection Character region extracting method and apparatus capable of implementing the method Patent #: 4903311 InventorsAssigneeApplicationNo. 359296 filed on 05/31/1989US Classes:382/151, Alignment, registration, or position determination382/156, Neural networks382/289Determining amount an image is rotated or skewedExaminersPrimary: Boudreau, Leo H.Assistant: Johns, Andrew W. International ClassG06K 009/00AbstractThe 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 is used to extract lines using horizontal bitmap sums, and then individual symbols using vertical bitmap sums, using thresholds with each of the sums. The separated symbols are then appropriately trimmed and sealed to provide individual normalized symbols. A Decision Module comprising a Feed-Forward Neural network and a sequential decision arrangement determines the "up", "down" or "indeterminate" orientation of the text after a variable number of symbols have been processed. The system can then compare the determined orientation with a database to further determine if the object is in the "right-side up" "upside down" or "indeterminate" orientation.Other References
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