Mobile Image Capture Module for Automated Shipping Label Processing
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Solution Overview
Problem
Conventional Internet-based shipping and delivery networks face delays and increased costs due to the need for manual re-labeling of packages at scanning points, which is time-consuming and inefficient, especially for shipments without network-assigned shipping labels.
Innovation Solution
Implementing a mobile image capture and processing system that digitally images shipping documents at the point of pickup, processes the images, and transmits them to a network for recognition and storage, allowing for the generation of intelligent machine-readable labels that can be applied at scanning points, enabling efficient tracking and routing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual re-labeling of packages is performed at scanning points, then shipping labels can be assigned and processed, but delivery time increases and processing costs increase
Solution Approach 1:
The system performs preliminary actions by capturing images of shipping documents at the point of pickup and processing them through OCR recognition before the package reaches the scanning point. This advance processing eliminates the need for manual re-labeling later, directly reducing delivery time while ensuring label accuracy is maintained
Solution Approach 2:
The patent replaces the mechanical manual re-labeling process with an automated optical character recognition system. Image capture devices and OCR software automatically extract shipping information from documents and generate labels, substituting human labor with automated technology to reduce processing time while maintaining reliability
2Reliability
If manual re-labeling of packages is performed at scanning points, then shipping labels can be assigned and processed, but processing costs increase
Solution Approach 1:
The system enables self-service by allowing the shipping document images to be automatically captured, processed, and converted into machine-readable labels without requiring manual intervention at the scanning point. The OCR system and automated label generation perform the work that would otherwise require paid human labor, reducing processing costs while maintaining processing reliability
Solution Approach 2:
Manual re-labeling operations are replaced with automated image processing and OCR technology. This substitution eliminates the need for human workers to manually create and attach labels at scanning points, directly reducing labor costs while ensuring consistent and reliable label processing through automated systems
3Loss of time
If digital image capture and processing is implemented at pickup points, then delivery time is reduced and tracking is improved, but device complexity increases
Solution Approach 1:
The patent introduces an intermediary processing layer that captures images at pickup points and processes them through OCR recognition before transmission to the central system. This intermediary step enables early processing and tracking without requiring the pickup devices to be overly complex, as the heavy processing is distributed to centralized servers that handle the computationally intensive OCR and data management tasks
4Productivity
If automated label generation from image processing is implemented, then productivity is improved, but measurement precision requirements increase
Solution Approach 1:
The system implements feedback mechanisms where the OCR recognition results are validated and verified before final label generation. The automated system can detect and correct recognition errors, and the feedback loop ensures that only accurately recognized information is used for label creation. This maintains high productivity while ensuring the precision requirements are met through systematic error checking and correction
Data Source
AI summary
A digital image capture and processing module for use with an Internet-based shipping, tracking and delivery network. The module includes a housing having a light transmission aperture with an optically transparent imaging window mounted thereover. A digital camera board supports an area-type color image sensing array, sensing array control electronics, and image capture and buffering electronics. An imaging lens assembly supported within said housing and having image forming optics with a field of view (FOV) on the area-type color image sensing array. A plurality of broad-band LEDs are supported within said housing for producing a field of broad-band illumination. A light focusing reflector is operably mounted for focusing the field of broad-band illumination. A digital image-processing subsystem supports image capture, processing and display functions, as well as digital image file transmission functions within the module. A system control subsystem controls and/or orchestrates the operation of components within the module; and a plurality of mode selection buttons are provided on the housing so that, upon depression, control signals are generated and are to the system control subsystem.