Obstruction Detector Using Virtual Boundary Comparison
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Solution Overview
Problem
Existing form reading systems, particularly those with open platens, face challenges in detecting and reacting to foreign obstructions such as shadows, light reflections, or human hands that obscure parts of the digitized image, leading to incorrect form reading and potential rejection.
Innovation Solution
The system captures a digitized image of the form and uses pre-stored model information about known boundaries and patterns to detect anomalies, such as unexpected edges or contrast changes, to identify foreign obstructions, which can be highlighted and signaled to the user for removal, using a combination of printed and virtual boundaries, optical intensity, and infra-red light to ensure accurate reading.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If open platen form readers are used to allow form insertion, then ease of operation is improved, but foreign obstructions may obscure parts of the digitized image leading to reading errors
Solution Approach 1:
The system performs preliminary detection of foreign obstructions by comparing captured image boundaries against stored model boundaries before attempting to read the form. This preliminary action identifies and flags obstructions that would otherwise cause reading errors, allowing the system to alert users and prevent inaccurate readings.
Solution Approach 2:
The system provides feedback to users by displaying detected foreign obstructions and their locations on the form image. This feedback mechanism allows users to remove or correct obstructions, thereby maintaining reading accuracy while preserving the ease of open platen insertion.
2Measurement precision
If border marks are added to forms to detect foreign obstructions, then measurement precision is improved, but manufacturing complexity increases
Solution Approach 1:
The system uses a universal boundary detection algorithm that works with any form type by comparing captured images against stored model boundaries. This multi-functional approach eliminates the need for form-specific border marks, maintaining measurement precision while avoiding increased manufacturing complexity.
Solution Approach 2:
Instead of adding physical border marks to each form, the system creates a digital copy or model of the form boundaries and uses this for comparison. This virtual boundary approach achieves the same obstruction detection precision as physical borders would provide, without any additional manufacturing requirements.
3Reliability
If the system highlights and signals foreign obstructions, then reliability of form reading is improved, but device complexity increases
Solution Approach 1:
The system uses a software-based image comparison intermediary that mediates between the captured form image and the reading process. This intermediary layer detects boundaries and identifies obstructions without requiring additional hardware components, improving reliability while minimizing increases in device complexity.
Solution Approach 2:
The system replaces potential mechanical or complex optical obstruction detection mechanisms with a software-based image processing approach. By using digital boundary comparison and pixel analysis, the system achieves reliable obstruction detection without adding mechanical complexity to the device structure.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution effectively detects and alerts users to foreign obstructions, allowing for their removal and ensuring accurate processing of forms by highlighting the obstruction area and providing a message or visual cues, thereby improving the reliability of form reading systems.
Implementation Method 1
reading a form begins with a photo-sensitive device or camera or the like that captures an image of the form
Implementation Method 2
using a combination of printed and virtual boundaries, optical intensity, and infra-red light to ensure accurate reading
Data Source
AI summary
An optical reader of a form is discussed where the form has a stored known boundary or boundaries. When the boundaries in a captured image do not match those of the stored known boundaries, it may be determined that an obstruction exists that will interfere with a correct reading of the form. The boundary may be printed, blank, and may include quiet areas, or combinations thereof in stored known patterns. A captured image of the form is compared to retrieved, stored boundary information and differences are noted. The differences may be thresholded to determine if an obstruction exists. If an obstruction is detected, the operator may be signaled, and the location may be displayed or highlighted. The form may be discarded or obstruction may be cleared and the form may be re-processed.