Automatic Edge and Object Detection for Machine Vision Job Setup
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Solution Overview
Problem
Current machine vision systems require significant user input to define items of interest, which can be cumbersome, especially for multiple tasks.
Innovation Solution
A method and system that automatically determine an item of interest within an image file and recommend appropriate tools for processing, reducing the need for user input by using image analysis techniques such as edge detection and pixel analysis to identify items like barcodes or physical objects, and display them on a screen with corresponding tool recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If automatic item determination is implemented, then user time and interaction are reduced, but system complexity increases
Solution Approach 1:
The system automatically determines the item of interest by analyzing the image file without requiring user input. The processors autonomously identify items such as barcodes, QR codes, or physical objects and select appropriate machine vision tools, enabling the system to serve itself rather than relying on user guidance.
Solution Approach 2:
The system performs preliminary analysis of the image file to automatically determine the item of interest before the user needs to specify it. By pre-identifying items and pre-selecting appropriate tools based on image content, the system eliminates the need for user input during the setup phase.
2Ease of operation
If automatic tool selection is implemented, then ease of operation is improved, but measurement precision may be affected
Solution Approach 1:
The system displays the determined item of interest and the selected appropriate tool to the user on a display screen. This feedback mechanism allows users to verify the automatic selections and make corrections if needed, ensuring both ease of operation and accuracy in tool selection.
Solution Approach 2:
The system changes parameters based on the analyzed image content - specifically, it adjusts the selection of machine vision tools according to the type of item detected (barcode, QR code, or physical object). This dynamic parameter adjustment ensures appropriate tool selection while maintaining ease of operation.
Data Source
AI summary
Systems and methods for automatic identification and presentation of edges, shapes and unique objects in an image used for machine vision job setup are disclosed herein. An example method includes receiving, by one or more processors, an image file. The method further includes automatically determining, by the one or more processors, an item of interest within the image file. The method further includes analyzing, by the one or more processors, the item of interest to determine an appropriate tool for processing the item of interest. The method further includes displaying, by the one or more processors, on a display screen: (i) an image corresponding to the image file, (ii) an indication of the item of interest, and (iii) an indication of the appropriate tool.