# US 11,112,238 B2 · Method and apparatus for scanning object > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,112,238 B2 - Document ID: US11112238B2 - Status: Granted - Kind: B2 - Application number: 15/164,955 - Filed: 2016-05-26 - Published: 2017-01-12 - Granted: 2021-09-07 - Earliest claimed: 2015-07-07 - Assignees: Quality Vision International, Inc. - Applicants: Quality Vision International Inc. - Inventors: Edward Tarry Polidor; Jeffrey Blood; Daniel C. Abbas - Web page: https://patentgrep.com/patent/US11112238B2 ## CPC - G01B 11/25: by projecting a pattern, e.g. {one or more lines,} moiré fringes on the object (G01B11/255 takes precedence {; image analysis for depth or shape recovery G06T7/50}) - G01B 5/008: using coordinate measuring machines - G01B 5/066: {of coating} - G01B 11/0616: {of coating} - G01B 11/245: using a plurality of fixed, simultaneously operating transducers ({G01B11/2408 - G01B11/2425, } G01B11/255 take precedence) - G01B: MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS ## Abstract Method and apparatus for scanning surfaces of a three-dimensional object employ a first sensor to acquire first data points and a second sensor to acquire second data points. The first sensor has a relatively lower accuracy and faster data point acquisition rate than the second sensor, and the second data points are assigned a higher weighting than the first data points. A three-dimensional coordinate point cloud is generated based on the both the first and second data points and their respective weighting. ## Claims ### Claim 1 A method comprising: (a) scanning surfaces of a three-dimensional object with a first sensor to acquire first data points representative of surfaces that have been scanned with the first sensor, and adding the first data points to a three-dimensional coordinate point cloud; (b) scanning surfaces of the three-dimensional object with a second sensor to acquire second data points representative of surfaces that have been scanned with the second sensor, and adding the second data points to the three-dimensional coordinate point cloud; (c) wherein the first sensor has a lower accuracy and a faster data point acquisition rate than the second sensor, and the second data points are assigned a higher weighting than a weighting assigned to the first data points; and (d) basing the three-dimensional coordinate point cloud on weighted first and second data points. ### Claim 2 (depends on 1) The method of claim 1, wherein the first sensor comprises an optical area sensor or a 3D laser scanner. ### Claim 3 (depends on 2) The method of claim 2, further comprising adjusting a level of light projected on the three-dimensional object based on reflectivity of a surface being scanned. ### Claim 4 (depends on 3) The method of claim 3, wherein the optical area sensor comprises at least one of a camera and a fringe projector. ### Claim 5 (depends on 1) The method of claim 1, wherein the second sensor comprises at least one of an optical point or line sensor, a point scanning laser probe and a touch probe sensor. ### Claim 6 (depends on 1) The method of claim 1, further comprising comparing the three-dimensional coordinate point cloud to a reference model and determining any deviations therebetween. ### Claim 7 (depends on 1) The method of claim 1, wherein assigned weightings of the first and second data points are proportional to respective accuracies of the first and second sensors. ### Claim 8 (depends on 1) The method of claim 1, wherein standard deviation values of the first and second data points are determined, and assigned weightings of the first and second data points are based on the reciprocal of the respective standard deviation values. ### Claim 9 (depends on 1) The method of claim 1, wherein the three-dimensional object is scanned with the first sensor multiple times, with acquired first data points from each scan being added to the three-dimensional coordinate point cloud. ### Claim 10 (depends on 9) The method of claim 9, wherein the three-dimensional object is supported on a rotatable support, and the object is scanned with the first sensor at multiple rotatable support positions. ### Claim 11 (depends on 1) The method of claim 1, wherein the three-dimensional object is scanned with the first sensor, followed by scanning of the three-dimensional object with the second sensor, or the three-dimensional object is scanned with the second sensor, followed by scanning of the three-dimensional object with the first sensor. ### Claim 12 (depends on 1) The method of claim 1, wherein only selected surfaces of the three-dimensional object are scanned with the second sensor. ### Claim 13 (depends on 12) The method of claim 12, wherein said selected surfaces include local portions of the three-dimensional object for which first data points potentially have low density or are lacking. ### Claim 14 (depends on 12) The method of claim 12, wherein said selected surfaces include local portions of the three-dimensional object including complex surface geometry. ### Claim 15 (depends on 1) The method of claim 1, further comprising scanning surfaces of the three-dimensional object with a third sensor to acquire third data points representative of surfaces that have been scanned with the third sensor, and adding the third data points to the three-dimensional coordinate point cloud, (a) wherein the third sensor has a different accuracy and speed of data point acquisition than the first and second sensors, and the third data points are assigned a weighting based on the third sensor accuracy relative to the first and second sensors. ### Claim 16 An apparatus comprising: (a) a first sensor that scans surfaces of a three-dimensional object to acquire first data points representative of surfaces that have been scanned with the first sensor; (b) a second sensor that scans surfaces of the three-dimensional object with a second sensor to acquire second data points representative of surfaces that have been scanned with the second sensor, wherein the first sensor has a lower accuracy and a faster data point acquisition than the second sensor; and (c) a module that collects the first and second data points, adds the first and second data points to a three-dimensional coordinate point cloud, and bases the three-dimensional coordinate point cloud on weightings of the first and second data points, with the second data points having a higher weighting than a weighting of the first data points. ### Claim 17 (depends on 16) The apparatus of claim 16, wherein the first sensor comprises an optical area sensor. ### Claim 18 (depends on 17) The apparatus of claim 17, wherein the optical area sensor comprises at least one of a camera and a fringe projector. ### Claim 19 (depends on 17) The apparatus of claim 17, further comprising a light adjustor that adjusts a level of light projected on the three-dimensional object based on reflectivity of a surface being scanned. ### Claim 20 (depends on 17) The apparatus of claim 17, further comprising a rotatable support for the three-dimensional object, whereby the object is scanned with the first sensor at multiple rotatable support positions. ### Claim 21 (depends on 16) The apparatus of claim 16, wherein the second sensor comprises at least one of an optical point or line sensor, a point scanning laser probe and a touch probe sensor. ### Claim 22 (depends on 16) The apparatus of claim 16, wherein assigned weightings of the first and second data points are proportional to respective accuracies of the first and second sensors. ### Claim 23 (depends on 16) The apparatus of claim 16, further comprising a third sensor to acquire third data points representative of surfaces that have been scanned with the third sensor, wherein the module collects the third data points and adds them to the three-dimensional coordinate point cloud, wherein the third sensor has a different accuracy and speed of data point acquisition than the first and second sensors, and the third data points are assigned a weighting based on the third sensor accuracy relative to the first and second sensors.