# US 2019/0244375 A1 · Intelligent Dishwashing Systems And Methods > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2019/0244375 A1 - Document ID: US20190244375A1 - Status: Published application - Kind: A1 - Application number: 15/887,566 - Filed: 2018-02-02 - Published: 2019-08-08 - Earliest claimed: 2018-02-02 - Assignees: Dishcraft Robotics, Inc. - Applicants: Dishcraft Robotics, Inc. - Inventors: Kerkil Choi; Paul M. Birkmeyer; Paul Baumgart; Kenneth M. Peters - Web page: https://patentgrep.com/patent/US20190244375A1 ## CPC - G06T 7/44: using image operators, e.g. filters, edge density metrics or local histograms - A47L 15/4295: {Arrangements for detecting or measuring the condition of the crockery or tableware, e.g. nature or quantity} - G06N 3/045: Combinations of networks - G06N 3/0464: Convolutional networks [CNN, ConvNet] - G06N 3/08: Learning methods - G06N 3/09: Supervised learning - G06T 7/0002: {Inspection of images, e.g. flaw detection} - G06T 7/0004: {Industrial image inspection} - G06T 7/11: Region-based segmentation - G06T 7/12: Edge-based segmentation - G06T 7/174: involving the use of two or more images - A47L 15/241: {the dishes moving in a horizontal plane} - A47L 2401/04: Crockery or tableware details, e.g. material, quantity, condition - G06T 2207/10024: Color image - G06T 2207/10048: Infrared image - G06T 2207/10064: Fluorescence image - G06T 2207/10152: Varying illumination - G06T 2207/20081: Training; Learning - G06T 2207/20084: Artificial neural networks [ANN] - G06T 2207/30108: Industrial image inspection - G06T 2207/30244: Camera pose - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - A47L: DOMESTIC WASHING OR CLEANING (brushes A46B; cleaning quantities of bottles or of other hollow articles of one kind B08B9/00; laundry D06F); SUCTION CLEANERS IN GENERAL (cleaning in general B08) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract Example intelligent dishwashing systems and methods are described. In one implementation, a system includes a light source that is configured to illuminate an article of dishware. An imaging system is configured to capture at least one image of the article of dishware. A processing system is configured to analyze the at least one image to determine a presence of a stain on the article of dishware. ## Claims ### Claim 1 An apparatus comprising: a light source configured to illuminate an article of dishware; an imaging system configured to capture at least one image of the article of dishware; and a processing system configured to analyze the at least one image to determine a presence of a stain on the article of dishware. ### Claim 2 (depends on 1) The apparatus of claim 1, further comprising a robotic actuator configured to change a pose of the article of dishware as viewed by the imaging system, wherein changing the pose of the article of dishware enables the imaging system to capture images of different portions of the article of dishware. ### Claim 3 (depends on 1) The apparatus of claim 1, further comprising an optical filter optically coupled to the light source or the imaging system, wherein the optical filter is configured to change the characteristics of light transmitted through the optical filter. ### Claim 4 (depends on 3) The apparatus of claim 3, wherein the optical filter is one of a polarizing filter, an infrared filter, or an ultraviolet filter. ### Claim 5 (depends on 1) The apparatus of claim 1, further comprising a plurality of light sources, wherein each of the plurality of light sources is configured to emit light with specific characteristics. ### Claim 6 (depends on 1) The apparatus of claim 1, wherein the light source is at least one of an ultraviolet light source, an infrared light source, or a white light source. ### Claim 7 (depends on 1) The apparatus of claim 1, further comprising a plurality of imaging systems, wherein each of the plurality of imaging systems is configured to capture an image of a substantially separate portion of the article of dishware. ### Claim 8 (depends on 1) The apparatus of claim 1, wherein the analysis is performed by a convolutional neural network associated with the processing system. ### Claim 9 (depends on 1) The apparatus of claim 1, wherein the processing system is further configured to detect a presence of a defect on the article of dishware. ### Claim 10 (depends on 1) The apparatus of claim 1, wherein the stain is delineated by the processing system using at least one of a bounding box, a contour, or a polygon. ### Claim 11 (depends on 1) The apparatus of claim 1, further comprising a cleanliness quantifier that is configured to determine a scale of cleanliness associated with the stain. ### Claim 12 (depends on 1) The apparatus of claim 1, further comprising a freshness estimator that is configured to determine an approximate age of the stain. ### Claim 13 A method comprising: illuminating, by a light source, an article of dishware; capturing, by an imaging system, at least one image of the article of dishware; and analyzing, by a processing system, the at least one image to determine a presence of a stain on the article of dishware. ### Claim 14 (depends on 13) The method of claim 13, further comprising changing a pose of the article of dishware as viewed by the imaging system, wherein changing the pose of the article of dishware enables the imaging system to capture images of different portions of the article of dishware. ### Claim 15 (depends on 13) The method of claim 13, further comprising filtering the light source, wherein the filtering changes the characteristics of light illuminating the article of dishware. ### Claim 16 (depends on 13) The method of claim 13, wherein the analysis is performed by implementing deep learning algorithms. ### Claim 17 (depends on 13) The method of claim 13, wherein the stain is delineated by at least one of a bounding box, a contour, or a polygon. ### Claim 18 (depends on 13) The method of claim 13, further comprising determining a cleanliness quantifier that is associated with the stain. ### Claim 19 (depends on 13) The method of claim 13, further comprising determining a freshness estimator associated with an approximate age of the stain. ### Claim 20 A method comprising: illuminating, by a light source, an article of dishware; capturing, by an imaging system, at least one image of the article of dishware; and analyzing, by a processing system, the at least one image to determine a presence of a defect on the article of dishware.