The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Nov. 03, 2020

Filed:

Feb. 16, 2016
Applicant:

Siemens Healthcare Diagnostics Inc., Tarrytown, NY (US);

Inventors:

Stefan Kluckner, Berlin, DE;

Yao-Jen Chang, Princeton, NJ (US);

Wen Wu, Kirkland, WA (US);

Benjamin Pollack, Jersey City, NJ (US);

Terrence Chen, Princeton, NJ (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 7/10 (2006.01); G06K 7/14 (2006.01); G06K 9/62 (2006.01); G01N 35/00 (2006.01); B01L 3/00 (2006.01);
U.S. Cl.
CPC ...
G06K 7/10722 (2013.01); G01N 35/00732 (2013.01); G06K 7/1413 (2013.01); G06K 7/1439 (2013.01); G06K 7/1491 (2013.01); G06K 9/629 (2013.01); B01L 3/5453 (2013.01); G01N 2035/00752 (2013.01); G06K 2209/19 (2013.01);
Abstract

Barcode tag conditions on sample tubes are detected utilizing side view images of sample tubes for streamlining handling in clinical laboratory automation systems. The condition of the tags may be classified into classes, each divided into a list of additional subcategories that cover individual characteristics of the tag quality. According to an embodiment, a tube characterization station (TCS) is utilized to obtain the side view images. The TCS enables the simultaneous or near-simultaneous collection of three images for each tube, resulting in a 360 degree side view for each tube. The method is based on a supervised scene understanding concept, resulting in an explanation of each pixel into its semantic meaning. Two parallel low-level cues for condition recognition, in combination with a tube model extraction cue, may be utilized. The semantic scene information is then integrated into a mid-level representation for final decision making into one of the condition classes.


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