# US 11,307,361 B2 · Methods for detection of contaminants on optical fiber connectors

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- Number: US 11,307,361 B2
- Document ID: US11307361B2
- Status: Granted
- Kind: B2
- Application number: 16/401,176
- Filed: 2019-05-02
- Published: 2019-11-07
- Granted: 2022-04-19
- Earliest claimed: 2018-05-02
- Assignees: Corning Research & Development Corporation
- Applicants: Corning Research & Development Corporation
- Inventors: Adam James Ruggles
- Web page: https://patentgrep.com/patent/US11307361B2

## CPC

- G01N 21/94: Investigating contamination, e.g. dust (G01N21/85 takes precedence)
- G06T 5/50: using two or more images, e.g. averaging or subtraction
- G01N 21/8851: {Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges (G01N21/8806 and G01N21/93 - G01N21/95692 take precedence; optical measurement of dimensions G01B11/00; optical scanning G02B26/10; image transformation G06T3/00; computerised image enhancement G06T5/00; image processing per se for flaw detection G06T7/0002)}
- G06T 5/20: using local operators
- G06T 7/0004: {Industrial image inspection}
- G06T 7/001: {using an image reference approach}
- G06T 7/11: Region-based segmentation
- G06T 7/12: Edge-based segmentation
- G06T 7/13: Edge detection
- G06T 7/136: involving thresholding
- G06T 7/62: of area, perimeter, diameter or volume
- G02B 6/385: {Accessories for testing or observation of connectors (means for centering or aligning the light guide within the ferrule with auxiliary facilities for movably aligning or adjusting the fibre within its ferrule, measuring position, eccentricity G02B6/3843; mechanical features associated with the optical testing of optical fibres G01M11/088)}
- G06T 2207/20132: Image cropping
- G06T 2207/20216: Image averaging
- G06T 2207/30108: Industrial image inspection
- G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q)
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G02B: OPTICAL ELEMENTS, SYSTEMS OR APPARATUS

## Abstract

Methods for detecting contaminants on optical fiber connectors incorporate statistically based routines that include processing of one or more digital images to dynamically determine fiber locations and boundaries, detect contamination in fiber locations, dynamically detect ferrule boundaries, detect contamination in ferrule locations, and collect resulting data. Sequential masking and detection permits detection of contaminants in a first region non-coincident with a first mask image, and in a second region non-coincident with a second mask image. Dynamic determination of locations and boundaries for structures such as fibers, ferrules, and pins or pinhole features address limitations associated with static determination of locations and boundaries for these structures. Specific routines or routines are provided for single- and multi-fiber connectors, including single fiber connectors having physical contact and angled physical contact polishes.

## Claims

### Claim 1

A method for identifying contaminants from a digital image of an end of an optical fiber connector in which one or more optical fibers is surrounded by a ferrule, wherein each of the one or more optical fibers includes a respective fiber core and associated fiber cladding, the method comprising:
defining a first mask image representing a first portion of the end of the optical fiber connector;
detecting contaminants in at least one first region of the digital image, wherein the at least one first region is non-coincident with the first mask image;
defining a second mask image representing a second portion of the end of the optical fiber connector; and
detecting contaminants in at least one second region of the digital image, wherein the at least one second region is non-coincident with the second mask image;
wherein the first mask image is non-coincident with the second mask image.

### Claim 2 (depends on 1)

The method of claim 1, wherein the first mask image encompasses the fiber core and associated fiber cladding of at least one optical fiber of the one or more optical fibers, and the second mask image corresponds to the ferrule.

### Claim 3 (depends on 2)

The method of claim 2, wherein the optical fiber connector further comprises a plurality of pins or pinhole features, and the first mask image additionally encompasses the plurality of pins or pinhole features.

### Claim 4 (depends on 1)

The method of any of claim 1, further comprising establishing at least one point of reference on the end of the optical fiber connector, and utilizing the at least one point of reference in at least one of defining the first mask image or defining the second mask image.

### Claim 5 (depends on 4)

The method of claim 4, wherein the at least one point of reference comprises a center location of the fiber core of the one or more optical fibers.

### Claim 6 (depends on 4)

The method of claim 4, wherein the end of the optical fiber connector further comprises a plurality of pins or pinhole features, and the at least one point of reference comprises a center location of at least one pin or pinhole feature of the plurality of pins or pinhole features.

### Claim 7 (depends on 4)

The method of claim 4, wherein the at least one point of reference comprises an outer boundary of the ferrule.

### Claim 8 (depends on 1)

The method of claim 1, further comprising processing the digital image to extract the first mask image or the second mask image, wherein following said processing, said detecting of contaminants in the at least one first region or the at least one second region comprises:
for each kernel size of a plurality of different kernel sizes, performing two-dimensional ensemble averaging and utilizing a result of the two-dimensional ensemble averaging to normalize the digital image to yield an ensemble normalized image;
for each kernel size of the plurality of different kernel sizes, performing two-dimensional median averaging and utilizing a result of the two-dimensional median averaging to normalize the digital image to yield an median normalized image;
applying a first universal threshold value across each ensemble normalized image to generate a thresholded ensemble normalized image with a binary representation of contaminants relative to areas devoid of contaminants;
applying a second universal threshold value across each median normalized image to generate a thresholded median normalized image with a binary representation of contaminants relative to areas devoid of contaminants;
for each kernel size of the plurality of different kernel sizes, summing the binary representation of contaminants of the thresholded ensemble normalized image and the binary representation of contaminants of the thresholded median normalized image to yield a contamination probability image including a summation of contamination probability;
for each kernel size of the plurality of different kernel sizes, closing boundaries of any continuous contaminant areas that are present in the contamination probability image adjacent to inter-regional edges and/or external edges of the end of the optical fiber connector, and filling any continuous contaminant areas that are present in the contamination probability image; and
identifying at least one of (i) number of closed and filled continuous contaminant areas, (ii) location of each closed and filled continuous contaminant area, and (iii) size of each closed and filled continuous contaminant area, present in the summed threshold normalized image of any one or more kernel sizes of the plurality of different kernel sizes.

### Claim 9 (depends on 1)

A non-transitory computer readable medium containing program instructions for causing a processor to perform a method according to claim 1.