Method and system for web-based optical defect detection using in-sensor uniformity correction

Abstract

Techniques are described in which an image capture device captures image data from web material. The image data comprises pixel values for the cross-web field of view of the image capture device. An analysis computer includes a computer-readable medium that stores parameters for a plurality of different normalization algorithms to normalize a cross-web background signal for the image capture device to a common desired value. The computer-readable medium further stores coefficients specifying a weighting for each of the plurality of normalization algorithms. The analysis computer computes a normalized value for each of the pixels of the image data as a weighted summation of results from application of at least two of the pixel normalization algorithms using the stored parameters.

Description

technical field [0001] This invention relates to automated inspection systems and, more particularly, to optical inspection of continuously moving webs. Background technique [0002] Vision inspection systems for analyzing moving webs have proven critical to modern manufacturing operations. Industries as diverse as metal fabrication, paper, nonwovens, and films rely on these automated inspection systems for product verification and in-line process monitoring. [0003] Automated visual inspection systems for products manufactured on a continuously moving web typically use one or more image capture devices to capture images of the web during manufacture. An analysis computer applies image processing algorithms to detect anomalies indicative of potential defects within the web. If an anomaly rises to a classification level of defect for a given product, the area of ​​the web containing the anomaly may be discarded or may be processed into other products that will not be affec...

AI Technical Summary

Problems solved by technology

[0005] In many cases, conventional vision inspection systems do not address within-device inspection non-uniformity associated with individual image capture devices

That is, intra-device non-uniformities in one or more image capture devices may cause substantially the same web anomaly to be classified differently because the anomaly is located within a different area of ​​the image capture device's field of view

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