3D Area Scan Measurement for Objects Longer Than the Field of View
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Solution Overview
Problem
Existing machine vision systems struggle to accurately capture and register multiple snapshots of objects longer than the field of view (FOV) of an area scan sensor, requiring computationally intensive post-processing to combine raw image data.
Innovation Solution
A system and method that uses an area scan sensor in conjunction with an encoder to track features of moving objects, capturing sequential snapshots until the object leaves the FOV, and combines these snapshots to derive overall dimensions without generating a complete image, using aggregate feature data to determine properties like length, width, and height.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Volume of moving object
If multiple snapshots are acquired to image objects longer than the FOV, then the full object can be captured, but the computational complexity increases due to the need to register and stitch together multiple 3D images
Solution Approach 1:
The patent divides the imaging process into sequential snapshots captured at different positions along the conveyor, with each snapshot covering a segment of the object. The encoder divides the FOV into multiple regions (e.g., first region and second region), and the system captures images of different object segments in different regions, then combines them to form a complete 3D model of the entire object.
Solution Approach 2:
The patent introduces an encoder as an intermediary device that provides precise positional information about the object and conveyor. This encoder data serves as a mediator to automatically determine when to capture snapshots and how to register them, eliminating the need for complex post-processing alignment algorithms while ensuring accurate stitching of multiple images.
2Ease of operation
If area scan sensors are used to capture 3D images, then snapshot acquisition is simplified without encoders, but objects longer than the FOV cannot be fully imaged in a single snapshot
Solution Approach 1:
The patent maintains continuous monitoring of the object as it moves through the FOV by using the encoder to track object position continuously. The system captures multiple snapshots at different positions along the conveyor path, ensuring that the entire object is covered without gaps. This continuous action approach allows the area scan sensor to effectively image objects longer than its static FOV.
Solution Approach 2:
The patent uses the encoder to predict when different portions of the object will enter and exit the FOV. Based on this preliminary knowledge of object position and conveyor speed, the system proactively captures snapshots at the optimal moments, ensuring complete object coverage while minimizing the number of images needed and simplifying the registration process.
3Length of moving object
If line scan sensors are used to capture arbitrarily long objects, then objects longer than FOV can be imaged, but encoders and motion measurement are required
Solution Approach 1:
The patent makes the encoder serve multiple functions: it not only provides motion information for timing snapshot acquisition but also enables automatic determination of object dimensions, position, and orientation. The same encoder data is used to trigger captures, register images, and calculate final measurements, eliminating the need for separate motion measurement systems and reducing overall device complexity.
Data Source
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AI summary
This invention provides a system and method for using an area scan sensor of a vision system, in conjunction with an encoder or other knowledge of motion, to capture an accurate measurement of an object larger than a single field of view (FOV) of the sensor. It identifies features/edges of the object, which are tracked from image to image, thereby providing a lightweight way to process the overall extents of the object for dimensioning purposes. Logic automatically determines if the object is longer than the FOV, and thereby causes a sequence of image acquisition snapshots to occur while the moving/conveyed object remains within the FOV until the object is no longer present in the FOV. At that point, acquisition ceases and the individual images are combined as segments in an overall image. These images can be processed to derive overall dimensions of the object based on input application details.