BACKGROUND

This disclosure relates generally to detection of contaminants on optical fiber connectors, and more specifically to methods for processing digital microscopy images of ends of optical fiber connectors to enhance confidence in detection of contaminants thereon.

Optical fibers are useful in a wide variety of applications, including the telecommunications industry for voice, video, and data transmissions. Benefits of optical fiber include extremely wide bandwidth and low noise operation. In a telecommunications system that uses optical fibers, there are typically many locations where fiber optic cables carrying the optical fibers connect to equipment or other fiber optic cables. To conveniently provide these connections, fiber optic connectors are often provided on the ends of fiber optic cables.

A fiber optic connector typically includes a ferrule with one or more bores that receive one or more optical fibers. The ferrule supports and positions the optical fiber(s) with respect to a housing of the fiber optic connector. Thus, when the housing of the fiber optic connector is mated with another connector (e.g., in an adapter), the optical fiber in the ferrule is positioned in a known, fixed location relative to the housing. This allows an optical connection to be established when the optical fiber is aligned with another optical fiber in the mating connector.

At interconnections between fiber optic connectors, light exiting one or more optical fibers of a first fiber optic connector (of a first fiber optic cable) is introduced into core of one or more optical fibers within an adjacent, second fiber optic connector (of a second fiber optic cable). The light travels in respective cores of the optical fibers. If two optical fiber cores at an interconnection are misaligned, then transmission of a significant fraction of an optical signal from the core of the first optical fiber to the core of the second optical fiber may be inhibited, resulting in signal degradation at the interconnection. Furthermore, and more salient to the present disclosure, if contamination such as one or more pieces of debris is present on an end face of either of the fiber optic connectors that terminate the optical fibers, then transmission of optical signals from the core of the first optical fiber to the core of the second optical fiber optic may be inhibited. Unlike conductive wire cable connectors, dust, dirt, and other contaminants are a particular problem in optical connections because they interfere with the passage of light from one fiber to another, and signals borne by the light may be poorly transmitted, or not transmitted at all. Fiber optic connectors must therefore be kept clean to ensure long life and to minimize transmission loss and optical return loss at connection points.

The degree of inhibition (or attenuation) of signal transmission may depend on the distance of the closest particle from the core, particle size, and the number of particles. Even a single dust particle caught in the core area between two connectors may result in significant or even catastrophic degradation of signal transmission (e.g., increased insertion loss), depending on particle size. Dust particles as small as 1 micrometer (μm) in diameter at a connection point can significantly degrade performance, whereas particles at least 8 μm in diameter at a connection point can cause a complete failure of an optical system.

The IEC 61300-3-35 (“Basic Test and Measurement Procedures Standard for Fiber Optic Interconnecting Devices and Passive Components”) describes methods for quantitatively assessing the end face quality of a polished fiber optic connector, and contains specific cleanliness grading criteria to assess pass or fail certification for inspection of a fiber end face. Three basic measurements useful for assessing defects such as scratches or contamination include the location (e.g., distance from the core), size, and quantity. When defects are located in a fiber core, their influence on degradation of optical performance becomes more significant. The criteria in the IEC 61300-3-35 standard are based on the size and quantity scratches and other defects found in four different zones of a connector end face that are defined by the standard—namely, a core, cladding, adhesive, and contact zone. The foregoing four zones are a series of concentric circles that identify areas of interest on a connector end face, with the adhesive zone typically embodying epoxy or another adhesive to secure a glass optical fiber within the bore of a ceramic ferrule on which the contact zone is formed.FIG. 1Aillustrates an end face of a multi-mode fiber connector10showing IEC 61300-3-35 zones, namely the fiber core zone12(e.g., having a diameter range of 0-66 μm), the cladding zone14(e.g., having a diameter range of 66-120 μm), the adhesive zone16(e.g., having a diameter range of 120-135 μm), and the contact zone18(e.g., having a diameter range of 135-250 μm).FIG. 1Bdepicts an end face of a single-mode fiber connector20showing the fiber core zone22(e.g., having a diameter range of 0-25 μm), the cladding zone24(e.g., having a diameter range of 25-120 μm), the adhesive zone26(e.g., having a diameter range of 120-135 μm), and the contact zone28(e.g., having a diameter range of 135-250 μm. Given the difference in core size between single-mode and multi-mode optical fibers, IEC 61300-3-35 criteria vary based on connector type and fiber size. For example,FIG. 2Aprovides a table identifying certification thresholds for presence of scratches and defects in different zones of a multi-mode fiber, whileFIG. 2Bprovides a table identifying corresponding thresholds in different zones of a single-mode fiber.

Assessment of cleanliness for particulate contamination may be done before and after an optical component undergoes a cleaning process by an indirect method or a direct method. An indirect method involves transfer or extraction of particles from a surface under investigation (e.g., by detachment with a fluid medium, stripping, or tape lift), followed by evaluation with an analytical system. A direct method involves examination of surfaces without extraction or transfer of particles, such as by optical microscopy. Comparative advantages of direct analysis include simplicity and avoidance of sampling losses; however, challenges associated with direct analysis include distinguishing particles from a substrate for particles exhibiting low contrast, and the impracticality of identifying contaminants (e.g., particles) on surfaces with complex geometries.

Detection of contaminants on optical fiber connectors may also be complicated by the type (i.e., shape) of polish applied to the respective fiber and ferrule ends. Two main performance attributes influenced by fiber polish are insertion loss (referring to light lost at a connection due to misaligned cores and air gaps at connections) and back reflection (referring to light being reflected back toward the source, due to different refractive qualities of glass and air). The three main types of polishes that are currently in use include physical contact (PC), ultra physical contact (UPC), and angled physical contact (APC).FIG. 3is a schematic cross-sectional view of an interconnection between two optical fiber connectors30each including an optical fiber32within a ferrule34, and each being PC polished at an end35thereof with a flat profile. Such polishing causes optical fibers32of the respective connectors30as well as portions of the ferrules34of the respective connectors30to be in contact with one another.FIG. 4is a schematic cross-sectional view of an interconnection between two optical fiber connectors36each including an optical fiber38within a ferrule40, and each being UPC polished at an end41thereof with a steeply rounded profile. Such polishing causes optical fibers38of the respective connectors36to be in contact with one another, with little to no contact being made between portions of the ferrules40of the respective connectors36.FIG. 5is a schematic cross-sectional view of an interconnection between two optical fiber connectors42, each including an optical fiber44within a ferule46, and each being APC polished at an end thereof. Such polishing forms a fiber end portion47-1angled eight degrees from perpendicular (i.e., to reduce back reflection) and forms a ferrule end portion47-2that may be rounded, with an end of each connector42being asymmetric. The existence of different types of polishes increases the difficulty of adopting a single method for accurately and reliably identifying contaminants on end faces of optical fiber connectors by optical detection. APC polished connectors (e.g., APC polished LC- or SC-type single fiber connectors) are problematic, since the angled surface complicates identification of fiber/ferrule boundaries.

Separate from complications created by the existence of different polishes, contaminant detection is further complicated by the existence of different connector formats (e.g., single fiber and multi-fiber). Although commercially available software purports to inspect and quantify contamination on exposed fiber ends of multi-fiber connectors, to the same software does not inspect and quantify contamination on the ferrule surface of multi-fiber connectors.

Various types of single fiber and multi-fiber connector are known, with examples such as LC- and SC-type single fiber connectors and multi-fiber push-on (MPO)-type connectors being in widespread use. An exemplary SC-type single fiber connector50is shown inFIGS. 6A and 6B, and an exemplary MPO-type connector75is shown inFIGS. 7A and 7B.

As shown inFIGS. 6A and 6B, the connector50includes a ferrule51, a ferrule holder52from which the ferrule51extends, a housing53having a cavity60in which the ferrule holder52is received, and a connector body54configured to retain the ferrule holder52within the housing53. The ferrule51includes a small diameter bore section55(or “micro-hole”) in which an optical fiber56is secured using an adhesive material such as epoxy. The ferrule holder52includes a ferrule holder bore57from which the ferrule51extends. In particular, a rear portion58of the ferrule51is received in the ferrule holder bore57defined in (at least) a first portion59of the ferrule holder52, and is secured therein in a known manner. The ferrule holder52is biased to a forward position within the cavity60of the housing53by a spring61, which extends over a second portion62of the ferrule holder52having a reduced width compared to the first portion59. A rear portion of the housing53includes cut-outs or slots63on opposing surfaces to define a split shroud. The connector body54is generally tubular in shape with a medial shoulder64arranged between different diameter portions. Protrusions65(which may embody tabs) of the connector body54are configured to be snapped into the slots63of the housing53and retained therein by locking tabs66proximate to a leading edge of each slot63.

When the connector50is assembled as shown inFIG. 6A, a front end67of the ferrule51projects beyond a front end68of the housing53. The front end67of the ferrule51presents the optical fiber56(shown inFIG. 6B) for optical coupling with a mating component (e.g., another fiber optic connector; not shown), with the ferrule51serving to generally align the optical fiber56in an axial direction along a longitudinal axis70. The housing53includes a generally rectangular cross-sectional shape perpendicular to the longitudinal axis70, with two adjacent non-beveled corners72and two adjacent beveled corners74embodying transitions between four outer faces of the housing53proximate to the front end68of the housing53.

FIGS. 7A and 7Bshow the MPO-type connector75installed on a fiber optic cable76to form a fiber optic cable assembly77. The MPO-type connector75includes a ferrule78, a housing79received over the ferrule78, a slider or slide lock80received over the housing79, and a boot81received over the fiber optic cable76. The ferrule78is spring-biased within the housing79so that a front portion82of the ferrule78extends beyond a front end83of the housing79. Multiple optical fibers (not shown) carried by the fiber optic cable76extend through bores84(also referred to as micro-holes) defined in the ferrule78before terminating at or near a front end face85of the ferrule78. The optical fibers are secured within the ferrule78as described above, such as by using an adhesive material (e.g., epoxy). The optical fibers can be presented for optical coupling with optical fibers of a mating component (e.g., another fiber optic connector; not shown) when the housing79is inserted into an adapter, receptacle, or the like.

As shown inFIG. 7B, the MPO-type connector75also includes a ferrule boot86, guide pin assembly87, spring88, crimp body89, and crimp ring90. Optical fibers extend through an aperture defined through the ferrule boot86. The guide pin assembly87includes a pair of guide pins92extending from a pin keeper93. When the connector75is assembled, the pin keeper93is positioned against a back surface of the ferrule78, and the guide pins92extend through pin holes94(shown inFIG. 7A) provided in the ferrule78so as to project beyond the front end face85of the ferrule78. Both the ferrule78and guide pin assembly87are biased to a forward position relative to the housing79by the spring88, which is positioned between the pin keeper93and a portion of the crimp body89. The crimp body89includes latching arms95that engage recesses96in the housing79. The rear portion91of the ferrule78defines a flange that interacts with a shoulder or stop formed within the housing79for retention of the rear portion91of the ferrule78in the housing79. In a manner not shown in the figures, strength members (e.g., aramid yarn) from the fiber optic cable76may be positioned over an end portion97of the crimp body89that projects rearwardly from the housing79, and the strength members are secured to the end portion97by deformation of the crimp ring90. The boot81covers this region, as shown inFIG. 7A, and provides strain relief for optical fibers emanating from the fiber optic cable76by limiting the extent to which the connector75can bend relative to the fiber optic cable76.

The cleanliness of fiber optic connectors can be improved using cleaning equipment. In order to assess the cleaning performance of cleaning equipment, various image-based microscope inspection systems from commercial vendors can be used. While the hardware of commercially available microscope inspection systems may be sufficient to visualize contamination, the native analysis software accompanying the microscope inspection systems have shortcomings that can result in numerous deficiencies, including: (a) misidentification or inaccurate identification of a fiber within an image; (b) limited analysis regions; (c) misidentification of region of a ferrule surface as contamination; (d) failure to identify contamination present on a connector; and (e) incomplete contaminant size determination. These deficiencies can result in inaccurate data concerning contamination size and quantity, thereby hindering the assessment of cleaning performance of cleaning equipment. Thus, there is a need for improved methods (e.g., implementable in software) for detecting contaminants on optical fiber connectors.

SUMMARY

Aspects of the present disclosure provide methods for detecting contaminants on optical fiber connectors, employing processing of digital microscopy images of ends of optical fiber connectors to address deficiencies observed with commercially available software for use with optical inspection systems. In at least certain embodiments, methods incorporating statistically based routines 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. Such methods enable significant improvement in contaminant detection, boundary identification, and contaminant sizing assessment relative to commercially available software. Dynamic determination of locations and boundaries for structures such as fibers, ferrules, and (if provided) pins or pinhole features may address limitations associated with static determination of locations and boundaries for these structures, attributable to slight variations in imaged position of such structures. This may be due to factors such as connector manufacturing tolerances, optical imaging hardware tolerances or vibration, and/or presence of contamination proximate to connector region boundaries. Specific routines or routines may be utilized for different types of connectors, such as single fiber (e.g., LC or SC) connectors versus multi-fiber (e.g., MPO) connectors, and for different polishes (e.g., PC, UPC, or APC).

In an embodiment of the disclosure, a method is provided for identifying contaminants from a digital image of an end of an optical fiber connector that includes one or more optical fibers surrounded by a ferrule, wherein each of the one or more optical fibers includes a respective fiber core and associated fiber cladding. The method comprises defining a first mask image representing a first portion of the end of the optical fiber connector, and 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. The method further comprises 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. According to this embodiment, the at least one second region is non-coincident with the second mask image.

In another embodiment of the disclosure, a method is provided for identifying contaminants from a digital image of an end of an optical fiber connector that includes one or more optical fibers surrounded by a ferrule, wherein each of the one or more optical fibers includes a respective fiber core and associated fiber cladding. The method employs multiple “kernels” (i.e., small matrices) of different sizes. The method 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. The method further comprises, 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 a median normalized image. The method further comprises 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. The method further comprises 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. The method further comprises, 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. The method further comprises, 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 optical fiber connector, and filling any continuous contaminant areas that are present in the contamination probability image. The method further comprises 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.

In another embodiment of the disclosure, a method is provided for determining location of a fiber core from a digital image of at least a portion of an end of an optical fiber connector in which the fiber core is surrounded by fiber cladding and by a ferrule having a convex end surface. The method comprises generating a first binary image derived from the digital image of the end of the optical fiber, followed by determining a centroid position of the first binary image. The method further comprises extracting a subregion of the digital image substantially centered on the centroid position to generate a subregion image, with the subregion containing the fiber core. The method further comprises calculating two dimensional spatial gradient magnitude values of the subregion image to identify high intensity boundaries around (i) the fiber cladding and (ii) any contaminants optionally present on the fiber core and/or fiber cladding. The method further comprises applying a self-determining threshold from the two dimensional spatial gradient magnitude values to generate a second binary image including rings corresponding to at least some of the high intensity boundaries. The method further comprises filling the rings of the second binary image to yield filled rings, and comparing the filled rings to identify a position of the fiber cladding. The method further comprises centering a solid subregion of a new, third binary image to the position of the fiber cladding, wherein the solid subregion is matched in shape to the subregion of the digital image. The method further comprises generating a summation of common nonzero pixel values and corresponding pixel locations, and extracting maximum summation values and corresponding pixel locations. The method further comprises identifying location of the fiber core from pixel locations corresponding to the maximum summation values.

In another embodiment of the disclosure, a method is provided for determining a radius of a ferrule outer circular boundary from a digital image of at least a portion of an end of an optical fiber connector in which a fiber core is surrounded by fiber cladding and by a ferrule having a convex end surface. The method comprises calculating two dimensional spatial gradient magnitude values of the digital image to identify an outer high intensity boundary. The method further comprises extracting a radial profile from a center location of the fiber core to the outer high intensity boundary at each angular interval of a plurality of angular intervals. The method further comprises, for each radial profile, identifying a location of maximum two dimensional spatial gradient magnitude, and identifying a distance from said location to the center location to provide an estimated ferrule radius value. The method further comprises statistically filtering the estimated ferrule radius values to exclude all estimated ferrule radius values less than a mean estimated ferrule radius value minus two standard deviations from the mean estimated ferrule radius value, and computing a statistically filtered estimated ferrule radius value. The method further comprises determining a radius of the ferrule outer circular boundary from a difference between the statistically filtered estimated ferrule radius value and a selected distance if necessary to account for illumination roll-off proximate to the ferrule outer circular boundary.

In another embodiment of the disclosure, a method is provided for determining a ferrule outer boundary from a digital image of at least a portion of an end of an optical fiber connector (e.g., an APC polished connector) in which a fiber core is surrounded by fiber cladding and by a ferrule having an end surface non-perpendicular to a longitudinal axis of the fiber core. The method comprises performing ensemble normalization of the digital image to generate an ensemble normalized image. The method further comprises applying a universal threshold value across the ensemble normalized image to generate a binary image of sub-unity value features including an outer high intensity boundary. The method further comprises removing the largest single feature within an interior of the binary image. The method further comprises extracting a radial profile from a fiber core center position to the outer high intensity boundary at each angular interval of a plurality of angular intervals, yielding a plurality of radial profiles for the plurality of angular intervals. The method further comprises, for each radial profile, identifying a radius value for a non-zero pixel value farthest from the fiber core center position, yielding a plurality of radius values for the plurality of radial profiles. The method further comprises median filtering the plurality of radius values to remove outlying radius values and to yield median filtered radius values. The method further comprises polynomially fitting x coordinates of the median filtered radius values, and polynomially fitting y coordinates of the median filtered radius values. The method further comprises identifying an estimated ferrule outer boundary from corresponding pairs of polynomially fitted x and y coordinates. The method further comprises reducing a radial distance from each pair of polynomially fitted x and y coordinates to the fiber core center position by a selected value to yield a plurality of pairs of inset fitted x and y coordinates corresponding to coordinates of the ferrule outer boundary to facilitate contaminant detection.

In another embodiment of the disclosure, a method is provided for determining positions of multiple optical fibers from a digital image of at least a portion of an end of an optical fiber connector (e.g., an MPO connector) in which respective ends of the multiple fibers are arranged in a linear pattern on an end surface of a ferrule in the digital image. The method comprises smoothing the digital image by at least one of 2D ensemble normalization or 2D median normalization to generate a normalized image in which spurious pixels of the end surface of the ferrule exhibit reduced intensity. The method further comprises applying a threshold value across the normalized image, with the threshold value based on a selected percentage of a maximum pixel intensity value to identify a plurality of proposed fiber masks. The method further comprises calculating centroid x, y coordinates of each proposed fiber mask of the plurality of proposed fiber masks, identifying median difference values for centroid x coordinates of the plurality of proposed fiber masks, and identifying median difference values for centroid y coordinates of the plurality of proposed fiber masks. The method further comprises comparing a difference of centroid x and y coordinate values between adjacent proposed fiber masks to the median difference values for centroid x coordinates and centroid y coordinates, and responsive to such comparison: (i) removing any pairs of adjacent fiber masks of the plurality of proposed fiber masks embodying differences between centroid x and y coordinate values greater than a specified threshold than the median difference values for centroid x coordinates and centroid y coordinates, and (ii) spatially validating any other adjacent fiber masks of the plurality of proposed fiber masks embodying differences between centroid x and y coordinate values within a specified threshold of the median difference values for centroid x coordinates and centroid y coordinates to yield spatially validated fiber masks. The method further comprises, for any removed pairs of adjacent fiber masks that lie between spatially validated fiber masks, linearly interpolating positions of replacement fiber masks using the median difference values for centroid x coordinates and centroid y coordinates.

In another embodiment of the disclosure, a method is provided for determining center position of an individual optical fiber from a digital image of at least a portion of an end of an optical fiber connector in which one or more optical fibers is/are arranged in a ferrule, with the image showing a respective end of the one or more optical fibers on an end surface of the ferrule. The method comprises extracting a subregion of the digital image to generate a subregion image containing an individual optical fiber. The method further comprises performing ensemble normalization of the digital image to generate an ensemble normalized image. The method further comprises applying a universal threshold value across the ensemble normalized image to generate a binary image of sub-unity value features embodying a first fiber mask including multiple pixels each having x and y coordinates. The method further comprises for each pixel of the first fiber mask, investigating overlap with the first fiber mask by generating a circular binary mask centered on the pixel being investigated and tabulating a summation of nonzero pixel values in common with the first fiber mask as well as x and y coordinate values of the pixel being investigated. The method further comprises identifying center coordinates for a fiber core of the individual optical fiber as either (i) x and y coordinates for a single pixel being investigated embodying a maximum summation value or (ii) mean x and y coordinates for multiple pixels being investigated embodying equal maximum summation values.

In another embodiment of the disclosure, a method is provided for determining location of a pin or pinhole feature from a digital image of at least a portion of an end of an optical fiber connector (e.g., an MPO connector) in which one or more optical fibers is/are arranged on an end surface of a ferrule in the digital image, and the end surface includes the pin or pinhole features for promoting alignment with a mating optical fiber connector. The method comprises applying a universal threshold value across the digital image to generate a binary image of sub-unity value features. The method further comprises checking size and eccentricity of sub-unity value features to identify preliminary pin or pinhole feature masks each having perimeter pixel coordinates. The method further comprises filling any voids in the preliminary pin or pinhole feature masks by horizontal and vertical interpolation to form interpolated pin or pinhole feature masks. The method further comprises, for each interpolated pin or pinhole feature mask, calculating radial distances from each pixel of multiple pixels within the interpolated pin or pinhole feature mask to perimeter pixels of the interpolated pin or pinhole feature mask, comparing the radial distances to a median radial distance to the perimeter pixels for the multiple pixels, and validating pixels having corresponding radial distances within a specified distance of the median radial distance. The method further comprises, for each interpolated pin or pinhole feature mask, selecting a validated pixel corresponding to a maximum number of validated radial distances within a specified distance of the median radial distance as a center of the pin or pinhole feature.

In another embodiment of the disclosure, a method is provided for determining boundaries of a ferrule from a digital image of at least a portion of an end of an optical fiber connector in which respective ends of multiple optical fibers are arranged in a linear pattern on an end surface of the ferrule in the digital image, with the end surface further including pins or pinhole features. The method for determining boundaries of the ferrule comprises generating a first cropped image from the digital image, with the first cropped image being cropped along two edges thereof in a direction perpendicular to the linear pattern, wherein cropping locations of the first cropped image are determined from locations of the pins or pinhole features. The method further comprises, for each row of pixels of the cropped image perpendicular to the linear pattern, median filtering pixel intensity values to remove outlying pixel intensity values potentially attributable to contamination and to generate a first median filtered pixel intensity profile, followed by calculating gradient magnitude values of the first median filtered pixel intensity profile to generate a first gradient profile, and selecting minimum and maximum values from the first gradient profile to identify a first pair of opposing edges, respectively, of the ferrule. The method further comprises generating a second cropped image from the digital image, with the second cropped image being cropped along two edges thereof in a direction parallel to the linear pattern, wherein cropping locations of the second cropped image are determined from locations of the pins or pinhole features. The method further comprises, for each row of pixels of the cropped image parallel to the linear pattern, median filtering pixel intensity values to remove outlying pixel intensity values potentially attributable to contamination and to generate a second median filtered pixel intensity profile, followed by calculating gradient magnitude values of the second median filtered pixel intensity profile to generate a second gradient profile, and selecting minimum and maximum values from the second gradient profile to identify a second pair of opposing edges, respectively, of the ferrule. According to such method, the first pair of opposing edges and the second pair of opposing edges correspond to lateral boundaries of the ferrule.

Additional features and advantages will be set forth in the detailed description which follows, and in part will be readily apparent to those skilled in the technical field of optical connectivity. It is to be understood that the foregoing general description, the following detailed description, and the accompanying drawings are merely exemplary and intended to provide an overview or framework to understand the nature and character of the claims.

