Patent Publication Number: US-10789773-B2

Title: Mesh registration system and method for diagnosing tread wear

Description:
CROSS-REFERENCE TO RELATED APPLICATION(S) 
     The present application is a continuation-in-part claiming the benefit of U.S. Ser. No. 15/451,124 and claims the benefit of U.S. Ser. No. 62/631,830, filed Feb. 18, 2018, U.S. Ser. No. 62/742,407, filed Oct. 7, 2018, and U.S. Ser. No. 62/303,740, filed Mar. 4, 2016, which are all hereby incorporated by reference in their entirety. 
    
    
     BACKGROUND 
     Unevenly and overly worn tread on tires may reduce tire life and increase fuel consumption, besides being a hazard to drivers. Further, uneven wear on tire tread may waste tires and accelerate scrap growth creating stockpiles of tires posing a threat to public health, safety and the environment. 
     Many factors may cause such wear on tire tread including failure to rotate tires, underinflation of tires, alignment issues, and/or the like. It is estimated that tires may lose about 17.8 percent of their life potential due to underinflation. Factoring in the effects of misalignment and other issues, it is estimated that over a quarter of a tire&#39;s life may be lost due to uneven wear on tire tread amounting to approximately $37 in lost tread life per tire for over 300 million tires sold just in the United States. This adds up to over 11 billion dollars lost per year due to uneven wear on tire tread. 
     Despite the high cost of new tires, studies have shown that tires are not well maintained. The tire manufacturer trade association known as the Rubber Manufacturers Association (RMA) estimates that only 17 percent of people may be considered “Tire Smart” (i.e., understand basics of maintaining tires). Moreover, ten percent of U.S. motorists may drive on at least one bald tire with 50 percent of passenger vehicles estimated to be misaligned, and more than 50 percent of vehicles may be underinflated. 
     Overworn tires also may contribute to accidents. A study performed by the National Highway Traffic Safety Administration determined that tire-related crashes were more likely as tire tread wears. For example, the accident rate of a car was estimated at 2.4 percent with full tread depth compared to an accident rate of 26 percent when the tread is worn down (e.g., 0- 2/32 inch depth). Underinflated tires may also be a risk. Tires underinflated by 25 percent may more than triple the occurrence of an accident. 
     Tread of tires is characterized by a surface with grooves and tread blocks. The tread blocks are designed to wear down over time, and thus the depths of the grooves may be an indicator of the nature of wear. The span and depth of a tire groove may relate to tracking the motion causing wear. Many tire related problems are assessed by a tire professional examining a latitudinal swath (i.e., cross-section) of a tire. The tread depth gauge is the lifeblood of a tire professional. For example, fleet managers use the tread depth gauge to capture ongoing (e.g., weekly, monthly) measurements of tread wear for trend analysis, diagnosis of surface wear, and/or the like. Tire dealers also use tread depth gauges when evaluating tires for replacement and/or servicing. Using a tread depth gauge to monitor tire wear, however, is error prone and may be difficult to read. Additionally, this measurement process may be dirty and place a user into contact with hazardous materials such as carbon black, a known carcinogen. 
     Tire impression forensics is the science of matching tire tracks to tire type. However, current practice is limited to the use of websites and a guide. For example, the Tire Industry Association (TIA) and the Technology &amp; Maintenance Council (TMC) offer diagnostic guides that include characterizations of myriad different tire problems. Each tire problem includes a textual description of the issue with a sample photo, along with a recommended course of action. No tool currently exists in the marketplace, however, that provides the ability to electronically match worn tire tread track to tires and/or provide automatic tread identification. 
     Treadwear related diagnostics may be especially complicated to diagnose as tire tread may degrade in a three-dimensional (3D) pattern. Complicating the diagnostic issues, wear patterns may appear similar to one another, especially in early stages of wear. As such, a need exists for a system and method that provides an automated technique for three-dimensional analysis of tread wear. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Several embodiments of the present disclosure are hereby illustrated in the appended drawings. It is to be noted however, that the appended drawings only illustrate several typical embodiments and are therefore not intended to be considered limiting of the scope of the present disclosure. Further, in the appended drawings, like or identical reference numerals or letters may be used to identify common or similar elements, and not all such elements may be so numbered. The figures are not necessarily to scale, and certain features and certain views of the figures may be shown as exaggerated in scale or in schematic in the interest of clarity and conciseness. Various dimensions shown in the figures are not limited to those shown therein and are only intended to be exemplary. 
         FIG. 1A  is a block diagram of an exemplary automated tread registration system in accordance with the present disclosure. 
         FIG. 1B  is a block diagram of an exemplary user system for use in the automated tread registration system illustrated in  FIG. 1A . 
         FIG. 2  is a perspective view of an exemplary sensing system for use in the automated tread registration system illustrated in  FIG. 1A . 
         FIG. 3  is a diagrammatic view of the exemplary sensing system illustrated in  FIG. 2 . 
         FIG. 4A  is a side view of a three dimensional mesh of an object obtained using the automated tread registration system illustrated in  FIG. 1A . 
         FIG. 4B  is a top view of a tire swath of the three dimensional mesh illustrated in  FIG. 4A . 
         FIGS. 5A-5D  illustrate exemplary photogrammetry targets for use with in the exemplary automated tread registration system in accordance with the present disclosure. 
         FIG. 6  is a perspective view of the tire swath of  FIG. 5 . 
         FIG. 7  is a perspective view of a tire swath having a convex hull associated therewith. 
         FIG. 8  is a side view of a tire swath illustrating depth of grooves. 
         FIG. 9  is a perspective view of a tire swath illustrating depth of grooves. 
         FIGS. 10A, 10B and 10C  are perspective views of a tire swath within a bounding box. 
         FIGS. 11A-11E  illustrate orientation of a tire swath using the bounding box illustrated in  FIGS. 10A, 10B and 10C  to orient the tire swath in the X-axis, Y-axis and Z-axis. 
         FIG. 12  is a perspective view of a tire swath oriented in the X-axis, Y-axis and Z-axis. 
         FIG. 13A  is a diagrammatic view of a portion of tire having branding and associated designation as known within the industry. 
         FIG. 13B  is a diagrammatic view of a tire having known dimensions within the industry. 
         FIG. 14  is a perspective view of an oriented tire swath in accordance with the present disclosure. 
         FIGS. 15A-15E  illustrate orientation of a tire swath using grooves of the tire swath in accordance with the present disclosure. 
         FIGS. 16A-16D  illustrate orientation of a tire swath using tire pitch cycle in accordance with the present disclosure. 
         FIG. 17A  is a top view of a tire swath of a new tire. 
         FIG. 17B  is a top view of a tire swath of a wire having worn tread. 
         FIGS. 18A-18E  illustrate registration of a tire swath using grooves in accordance with the present disclosure. 
         FIGS. 19A and 19B  are diagrammatic views of a tire swath illustrating alignment of a tire, and in particular, effects of camber wear on the tire swath of a new tire and a tire having tread wear. 
         FIGS. 20A and 20B  are diagrammatic views of a protrusion of a tire, and in particular, effects of heel and toe wear on the protrusion and effects of rotation of tires to counteract wear. 
         FIGS. 21A-21C  illustrate identification of toe wear of a tire swath in accordance with the present disclosure. 
         FIG. 22  illustrates cleaning of a tire swath in accordance with the present disclosure. 
         FIGS. 23A-23L  illustrate an exemplary method for orienting, cleaning and scaling a tire swath in accordance with the present disclosure. 
         FIGS. 24A-24C  illustrate exemplary methods for scaling tire swaths by establishing section width, aspect ratio and/or wheel diameter in accordance with the present disclosure. 
         FIGS. 25A-25D  illustrate exemplary methods for orienting a tire swath in accordance with the present disclosure. 
         FIGS. 26A-26D  illustrate additional exemplary methods for orienting a tire swath in accordance with the present disclosure. 
         FIGS. 27A and 27B  illustrate an exemplary method for removing low quality data using a bounding box in accordance with the present disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     The present disclosure describes an automated tread registration system for measuring and/or analyzing tread wear. The present disclosure describes in detail the automated mesh registration system in relation to tread on tires, however, the system and method as described herein may be applied to other fields of interest including, but not limited to, shoe tread, tooth enamel wear, and/or any physical surface having a raised pattern and/or cut pattern capable of wear (e.g., damage, erosion, frictional destruction and/or the like). 
     Tread may be characterized by a surface having grooves. The surface may wear down over time and/or with use, and thus, span and/or depth of the grooves (i.e., distance from surface) may be an indicator of wear, nature of wear, diagnosis of wear, and/or aid in analysis for one or more action items (e.g., change tire, rotate tire). For example, a racing slick tire may be designed without grooves to maximize traction. Predefined holes, however, positioned circumferentially around the tire may provide an indicator of wear. 
     Generally, one or more three dimensional scans (e.g., formed by a series of overlapping 2D images or a laser) may be captured to form one or more surface model of an object. In some embodiments, a baseline scan may be obtained to form one or more baseline surface models. For example, the baseline scan may be from a new tire (i.e., no or substantially limited wear). The baseline surface model may be compared against secondary surface models as the tire is used. For example, one or more secondary scans may be obtained after the tire has been used a predetermined amount of time or for a predetermined amount of mileage to provide one or more secondary surface models. The secondary surface models may be compared against the baseline surface models for analysis and/or determination of one or more metrics (e.g., wear metrics) and identification of one or more action items including, but not limited to, tire replacement, tire inflation, tire rotation, wheel alignment, and/or the like. Wear metrics may include, but are not limited to, camber wear, overinflation, underinflation, heel toe wear, toe wear, and/or the like. In some embodiments, multiple secondary surface models may be compared against each other for analysis and/or determination of one or more wear metrics and of one or more action items. 
     Groove positioning, groove direction, groove width, groove depth or other tire elements, may be used to register baseline scans with the secondary scans. In some embodiments, he baseline scan may be used to form a three dimensional model (e.g., surface model) of the new tire. Using the secondary surface model(s), one or more scaled description of contours associated with grooves in the tread of the tire may be extracted from the scan. Using a 2D view, for example, of the three dimensional model of the new tire, the two dimensional grooves of the scans may be registered. For example, for each secondary scan, a three-dimensional contour of varying width and/or depth may be produced in relation to each groove until the two dimensional groove (i.e., width only) matches width of the three-dimensional groove of the three dimensional model. Depth of the groove may then be determined. Comparison of the baseline scan and/or secondary scans taken at distinct instants of time may include a multiple step process. 
     In some embodiments, a convex hull of the three dimensional model may be created for the baseline scan and/or secondary scans using the two dimensional images used to create the three dimensional model. The three dimensional models resulting from the scans may then be oriented and aligned. Groove depth may be determined using the convex hull. 
     Before describing various embodiments of the present disclosure in more detail by way of exemplary descriptions, examples, and results, it is to be understood that the embodiments of the present disclosure are not limited in application to the details of systems, methods, and compositions as set forth in the following description. The embodiments of the present disclosure are capable of other embodiments or of being practiced or carried out in various ways. As such, the language used herein is intended to be given the broadest possible scope and meaning; and the embodiments are meant to be exemplary, not exhaustive. Also, it is to be understood that the phraseology and terminology employed herein is for the purpose of description and should not be regarded as limiting unless otherwise indicated as so. Moreover, in the following detailed description, numerous specific details are set forth in order to provide a more thorough understanding of the disclosure. However, it will be apparent to a person having ordinary skill in the art that the embodiments of the present disclosure may be practiced without these specific details. In other instances, features which are well known to persons of ordinary skill in the art have not been described in detail to avoid unnecessary complication of the description. 
     Unless otherwise defined herein, scientific and technical terms used in connection with the embodiments of the present disclosure shall have the meanings that are commonly understood by those having ordinary skill in the art. Further, unless otherwise required by context, singular terms shall include pluralities and plural terms shall include the singular. 
     All patents, published patent applications, and non-patent publications referenced in any portion of this application are herein expressly incorporated by reference in their entirety to the same extent as if each individual patent or publication was specifically and individually indicated to be incorporated by reference. 
     As utilized in accordance with the concepts of the present disclosure, the following terms, unless otherwise indicated, shall be understood to have the following meanings: 
     The use of the word “a” or “an” when used in conjunction with the term “comprising” in the claims and/or the specification may mean “one,” but it is also consistent with the meaning of “one or more,” “at least one,” and “one or more than one.” The use of the term “or” in the claims and/or the specification is used to mean “and/or” unless explicitly indicated to refer to alternatives only or when the alternatives are mutually exclusive, although the disclosure supports a definition that refers to only alternatives and “and/or.” The use of the term “at least one” will be understood to include one as well as any quantity more than one, including but not limited to 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 30, 40, 50, 100, or any integer inclusive therein. The term “at least one” may extend up to 100 or 1000 or more, depending on the term to which it is attached; in addition, the quantities of 100/1000 are not to be considered limiting, as higher limits may also produce satisfactory results. In addition, the use of the term “at least one of X, Y and Z” will be understood to include X alone, Y alone, and Z alone, as well as any combination of X, Y, and Z. 
     As used in this specification and claim(s), the words “comprising” (and any form of comprising, such as “comprise” and “comprises”), “having” (and any form of having, such as “have” and “has”), “including” (and any form of including, such as “includes” and “include”) or “containing” (and any form of containing, such as “contains” and “contain”) are inclusive or open-ended and do not exclude additional, unrecited elements or method steps. 
     The term “or combinations thereof” as used herein refers to all permutations and combinations of the listed items preceding the term. For example, “A, B, C, or combinations thereof” is intended to include at least one of: A, B, C, AB, AC, BC, or ABC, and if order is important in a particular context, also BA, CA, CB, CBA, BCA, ACB, BAC, or CAB. Continuing with this example, expressly included are combinations that contain repeats of one or more item or term, such as BB, AAA, AAB, BBC, AAABCCCC, CBBAAA, CABABB, and so forth. The skilled artisan will understand that typically there is no limit on the number of items or terms in any combination, unless otherwise apparent from the context. 
     Throughout this application, the term “about” is used to indicate that a value includes the inherent variation of error that exists among the study subjects. Further, in this detailed description, each numerical value (e.g., temperature or time) should be read once as modified by the term “about” (unless already expressly so modified), and then read again as not so modified unless otherwise indicated in context. Also, any range listed or described herein is intended to include, implicitly or explicitly, any number within the range, particularly all integers, including the end points, and is to be considered as having been so stated. For example, “a range from 1 to 10” is to be read as indicating each possible number, particularly integers, along the continuum between about 1 and about 10. Thus, even if specific data points within the range, or even no data points within the range, are explicitly identified or specifically referred to, it is to be understood that any data points within the range are to be considered to have been specified, and that the inventors possessed knowledge of the entire range and the points within the range. Further, an embodiment having a feature characterized by the range does not have to be achieved for every value in the range, but can be achieved for just a subset of the range. For example, where a range covers units 1-10, the feature specified by the range could be achieved for only units 4-6 in a particular embodiment. 
     As used herein, the term “substantially” means that the subsequently described event or circumstance completely occurs or that the subsequently described event or circumstance occurs to a great extent or degree. For example, the term “substantially” means that the subsequently described event or circumstance occurs at least 90% of the time, or at least 95% of the time, or at least 98% of the time. 
     Software may include one or more computer readable instructions that when executed by one or more components cause the one or more component to perform a specified function. It should be understood that algorithms or process instructions described herein may be stored on one or more non-transitory computer readable medium. Exemplary non-transitory computer readable medium may include random access memory, read only memory, flash memory, and/or the like. Such non-transitory computer readable mediums may be electrically based, optically based, and/or the like. 
     Circuitry, as used herein, may be analog and/or digital components, or one or more suitably programmed processors (e.g., microprocessors) and associated hardware and software, or hardwired logic. Also, “components” may perform one or more functions. The term “component,” may include hardware, such as a processor (e.g., microprocessor), and application specific integrated circuit (ASIC), field programmable gate array (FPGA), a combination of hardware and software, and/or the like. The term “processor” as used herein means a single processor or multiple processors working independently or together to collectively perform a task. 
     Certain exemplary embodiments of the invention will now be described with reference to the figures. In general, such embodiments relate to automated methods for three-dimensional analysis and identification of tire related issues. However, the system and methods described herein may be applicable to other fields of interest having tread and/or wearing of tread. For example, the comparison of current tread life to original tread life may be used in a number of application, in addition to tire wear, including, but not limited to, shoe tread, stair tread, framing hammer deterioration, rubber utility mat deterioration, pistol grip deterioration, plyer jaw deterioration, rifling (e.g., shell casing) deterioration, and/or the like. Other fields of interest may include mechanical wear related to brake pads, pulleys, timing belts, drill bits, razor blades, brake rotors, teeth (e.g., chemical wear and/or mechanical wear), and/or the like. 
     In another example, by comparing tread wear on sneakers or shoes, an orthopedist or podiatrist may be able to diagnose improper stride in a patient and be able to recommend corrective measures based on the nature of wear of the tread of the sneaker or shoe. While this may be done with a qualitative analysis, the quantitative methods, as described herein, may provide analysis of small incremental changes and trends that may be detected. As such, assessments may be made as to whether corrective measures currently being used are improving, hindering or stagnating the issues and/or whether additional or slight alterations may further improve remedies. 
     In another example, analysis of shoe tread may be developed in a similar manner as described herein related to tire tread analysis. Generally, a quantitative analysis of shoe tread may be developed and/or measured using the techniques described herein. For example, analysis of current tread patterns as compared to original tread patterns may be performed to identify alterations in depth and height of the treads, grooves between the three-dimensional model of the current tread and the original tread, deformations to the tread pattern caused by wear (e.g., by performing edge detection as described in further detail herein). 
     Referring to the Figures, and in particular to  FIG. 1A , illustrated therein is a block diagram of an exemplary automated tread analysis system  10  in accordance with the present disclosure. Generally, the automated tread analysis system  10  may be configured to determine and/or analyze tread depth for one or more objects  12 . 
     The automated tread analysis system  10  may include a sensing system  14  configured to provide one or more overlapping images  16  (e.g., scans) of the object  12 , preferably taken from distinct and known capture locations. The object  12  (e.g., tire tread) generally includes one or more raised or cut patterns  18  having one or more grooves  20  (e.g., tire groove) and one or more protrusions  22  (e.g., tread block). The protrusions  22  may include one or more surfaces  24 . For example, if a tire is the object  12 , the protrusions  22  may be blocks of the tire (as known in the art), with the surface  24  of the protrusions  22  being a normalized surface. 
     Generally, the sensing system  14  may obtain and transmit the one or more images  16  to a user system  26  for determination of one or more surface models of the object  12 , tread depth of the grooves  20 , orientation of object  12  during use, registration of the object  12  using a baseline scan and/or a secondary scan as described in further detail herein, and/or the like. By analyzing variations in tread depth, orientation, registration and/or the like as described in further detail herein, the user system  26  may further identify one or more metrics (e.g., tread wear, camber wear, underinflation, overinflation, heel toe wear, and/or toe wear) and/or one or more actions items (e.g., rotate tires, provide new tire) based on the metric. The metric and/or the action items may be then provided in one or more reports  28 . 
     The sensing system  14  may be any system configured to provide one or more images  16  of the object  12  showing grooves  20  and protrusions  22  of the object  12 . For example, the sensing system  14  may include, but is not limited to, a laser scanning system (turntable/lab based and driveover systems), a high-density detector array (e.g., high density charge-couple device (CCD array), CMOS, array of photo-detection elements coupled to an imaging lens, and/or the like. Resolution of the images  16  may be such that a three-dimensional model of the object  12  may be created from the images  16 . It should be noted that the entirety of the object  12  need not be captured and/or modeled. For example, only a limited tire tread swath may be captured as reconstruction of the entire circumference of the tire may not be needed for diagnosis and/or action items. The size of the tire tread swath may be circumferentially long to enable orientation between images and registration as described in further detail herein. Additionally, the size of the tire tread swath may be based on particular diagnostics to be determined using the tire tread swath. For example, heel toe wear and toe alignment issues may be observed circumferentially, and as such, a longer swath may facilitate such measurement. 
     In some embodiments, the sensing system  14  may include one or more cameras mounted to and/or within the wheel well of an automobile. Cameras may be mounted in any direction such that each camera is able to provide one or more images  16  of the object  12  showing grooves  20  and protrusions  22  of the object  12 . When multiple cameras are used, the cameras can be positioned to provide overlapping images such that stereoscopic image analysis can be used to triangulate relative locations of the object  12  in 3D space for creating surface model(s) of the object  12 . In some embodiments, the sensing system  14  mounted to and/or within the wheel well may be configure to provide a circumferential view of the object  12  as the object  12  rotates about a fixed axis. 
       FIGS. 2 and 3  illustrate an exemplary sensing system  14  for use in the automated tread analysis system  10  in accordance with the present disclosure. In some embodiments, the sensing system  14  may include an imaging, documenting and analyzing (IDA) system  30  further described in detail in U.S. Pat. No. 9,291,527, which is hereby incorporated by reference in its entirety. Generally, the IDA system  30  includes one or more digital imaging devices  32  and a guidance dolly  34 . The digital imaging device  32  in conjunction with the guidance dolly  34  may be configured to acquire a plurality of sequential, overlapping, two-dimensional scans (e.g., images) of at least a portion of the object  12 . The guidance dolly  34  may serve as an acquisition platform in that the digital imaging device  32  may be configured to move along a predefined trajectory and at a predefined spacing from the object  12  on the guidance dolly  34 . The defined trajectory may include a linear path, a helical path, a spiral path, a fanciful path, and/or the like. 
     The digital imaging device  32  may include one or more lens  36 , one or more image sensors  38 , imaging device control circuitry  40 , and a digital memory  42 . The len(s)  36  may function to project the field of view onto the image sensor(s)  38 . In some embodiments, the digital imaging device  32  may be a Smartphone having a single or multiple cameras. The image sensor(s)  38  may convert the field of view into a two-dimensional digitized image, and the imaging device control circuitry  40  may convert each two-dimensional digitized image  16  into a corresponding digital image file, as well-known in the relevant art. The digital memory  42  may be used for storing the acquired and converted digital image files. 
     As shown in  FIG. 3 , a dolly contact surface  46  may be configured to provide placement of the guidance dolly  34  into physical contact with a surface  48  of the object  12 , as indicated by arrows  50 . During operation, the digital imaging device  32  may be placed against a guidance surface  52 , as indicated by arrows  54 , for acquisition of digital images. Further, a guidance channel  56  extends between the guidance surface  52  and the dolly contact surface  46  such that the digital imaging device  32  may be able to image the object  12  from various positions on the guidance surface  52 . The guidance channel  56  may also provide for insertion of the lens  36  for imaging devices wherein the lens  36  protrudes. As the digital imaging device  32  is positioned against the guidance surface  52  with the lens  36  positioned adjacent to or inside of the guidance channel  56 , the guidance dolly  34  may function to maintain the digital imaging device  32  at a desired distance and/or orientation relative to the surface of the object  12 . 
     The guidance dolly  34  may serve as the acquisition platform to provide a systematic way to acquire images  16  from the digital imaging device  32  when moving along a pre-defined trajectory. The predefined trajectory may enable extraction of an adequate sample of the object  12  and, in some embodiments, may provide for adequate photogrammetric angle separation (i.e., parallax) and image matching between successive image captures. The guidance dolly  34  may provide support at the surface of the object  12  so as to maximize stability of the digital imaging device  32  relative to the object  12 , while images are being acquired. 
     In some embodiments, an IDA software application  58  within a software module  60  of the IDA system  30  may be capable of digitally converting the digital images  16  into one or more three dimensional data image files representative of the surface  48  of the object  12  (e.g., surface models). In some embodiments, conversion of the digital images  16  into one or more three dimensional data image files may be included within the user system  26 . In some embodiments, the digital imaging device  32  may further include a wired or wireless communication module  62  (e.g., Bluetooth module), for communicating with the user system  26  via a network  64 . The network  64  may be almost any type of network. For example, the network  64  may interface by optical and/or electronic interfaces, and/or may use a plurality of network topographies and/or protocols including, but not limited to, Ethernet, TCP/IP, circuit switched paths, and/or combinations thereof. For example, in some embodiments, the network  64  may be implemented as the World Wide Web (or Internet), a local area network (LAN), a wide area network (WAN), a metropolitan network, a wireless network, a cellular network, a Global System for Mobile Communications (GSM) network, a code division multiple access (CDMA) network, a 3G network, a 4G network, a 5G network, a satellite network, a radio network, an optical network, a cable network, combinations thereof, and/or the like. It is conceivable that in the near future, embodiments of the present disclosure may use more advanced networking topologies. 
     Once images  16  are acquired, the digital imaging device  32  and/or the user system  26  may function to generate a three-dimensional mesh (e.g., one or more surface models), in accordance with best videogrammetry practice. For example, software including, but not limited to 123D Catch available from Autodesk having a principal place of business in San Rafael, Calif., Photosynth available from Microsoft having a principal place of business in Redmond, Wash., and/or the like can be used to convert the images  16  into the three-dimensional mesh. 
     Referring to  FIGS. 1A and 1B , the user system  26  may be capable of interfacing and/or communicating with the sensing system  14  via the network  64 . The user system  26  may include, but is not limited to implementation as a variety of different types of computer systems, such as a server system having multiple servers in a configuration suitable to provide a commercial based business system (such as a commercial web-site and/or data center), a personal computer, a smart phone, a net-work capable television set, a tablet, an e-book reader, a laptop computer, a desktop computer, a network capable handheld device, a digital video recorder, a wearable computer, a ubiquitous computer, and/or the like. 
     Generally, the user system  26  may be implemented as a single or plurality of processors  66  working together, or independently to execute the logic as described herein. Exemplary processors  66  may include, but are not limited to, a digital signal processor (DSP), a central processing unit (CPU), a field programmable gate array (FPGA), a microprocessor, a multi-core processor, and/or combinations thereof, for example. It is to be understood, that in certain embodiments, using more than one processor  66 , the processors  66  may be located remotely from one another, in the same location, or comprising a unitary multi-core processor. The one or more processors  66  may be capable of reading and/or executing processor executable code and/or capable of creating, manipulating, retrieving, altering, and/or storing data structures into one or more memories  68 . 
     The one or more memories  68  may be capable of storing processor executable code. Additionally, the one or more memories  68  may be implemented as a conventional non-transitory memory, such as, for example, random access memory (RAM), a CD-ROM, a hard drive, a solid state drive, a flash drive, a memory card, an optical drive, combinations thereof, and/or the like, for example. 
     In some embodiments, the one or more memories  68  may be located in the same physical location as the one or more processors  66 . Alternatively, the one or more memories  68  may be located in a different physical location and communicate via a network, such as network  64 . Additionally, one or more of the memories  68  may be implemented as a “cloud memory” (i.e., one or more memories  68  may be partially or completely based on or accessed using a network). 
     The one or more memories  68  may store processor executable code and/or information comprising one or more databases and program logic (i.e., computer executable logic). In some embodiments, the processor executable code may be stored as a data structure, such as a database and/or data table, for example. For example, one of the databases can be an image database storing three dimensional models of tire swaths. In another example, one of the databases may store orientation information for tire swaths. In another example, one of the databases may store registration information for tire swaths. In some embodiments, each database may be linked and/or interconnected with one or more databases such that data between each database may be shared and/or incorporated into a single database. 
     The one or more processors  66  may be configured to receive input (e.g., from a user) and provide output (e.g., one or more reports). The user system  26  comprising the one or more processors  66  may include one or more non-transient memory comprising processor executable code and/or software applications, for example. 
     In some embodiments, the user system  26  may be a smartphone with the processor  66  configured to run one or more applications. The one or more application may be downloaded by a user to the user system  26 . In some embodiments, the user system  26  may communicate with a server and/or cloud storage system when connected to a network (such as network  64 . To that end, the user system  26  may be configured to run when disconnected and/or connected to the network. 
     Referring to  FIGS. 1A, 1B, 4A and 4B , in use, the user system  26  may receive and/or capture one or more images  16  of the object  12  to collect information of the state of the object  12  at a particular instant of time. The images  16  may be uploaded to a cloud storage system, for example and converted to a three dimensional model  71  as discussed above. In some embodiments, the images  16  of the object  12  may be of a new and/or relatively new tire having little to no wear. The images  16  may be used to form a baseline surface model of the object  12 . In some embodiments, the images  16  of the object  12  may be captured subsequent to the baseline scan and be used to form a secondary surface model of a tire that has worn tread as compared to the baseline scan. 
     One or more tire swaths  70  may be obtained from a three dimensional mesh  71  (e.g., surface model) of the object  12  provided by the sensing system  14 . Tire swath  70  is a portion of the three-dimensional mesh  71 . For example,  FIG. 4A  illustrates a side view of the three dimensional mesh  71  of the object  12 . The area between lines  72  and  74  denotes a region where the tire swath  70  may be located.  FIG. 4B  illustrates a top view of the exemplary tire swath in  FIG. 4A . Generally, by analyzing images of the tire swath  70 , depth of the grooves  20  within the tire swath  70 , orientation of the tire swath  70  during use of the object  12 , and registration of the tire swath  70  as compared to similar and/or prior images, an analysis can be conducted (as set forth herein) to provide a diagnosis health of the object  12  and/or provide one or more action items related to the object  12  as described in further detail herein. 
     In some embodiments, an initial cleaning and/or rough orientation of the tire swath  70  may aid in subsequent processing steps. Referring to  FIG. 5A , noise and elements not associated with or a part of the object  12  (e.g., driveway) may be removed from the three-dimensional mesh  71 . In some embodiments, two or more targets  76  (i.e., known locations of the tire swath  70 ) in the Y axis may be determined. Portions of the tire swath  70  between targets  76  may be kept. For example, area A TS  between the connected components of the targets  76  may be kept with elements outside of this area A TS  being removed. Additionally, an incremental check of convexity across the tire swath  70  may be performed to remove non-convex portions  78 . For example, a determination of significant alterations in shape, color, and/or texture may be identified within the tire swath  70 , and associated portions removed. 
     Referring to  FIGS. 5A and 5B , the photogrammetry targets  76  and/or ground control points  174  may be one or more patterns  172  within the field of view of the digital imaging device(s)  32 . Such targets  76  and/or ground control points  174  may aid in converting a—projective surface to a metric surface, for example. In some embodiments, the targets  76  and/or ground control points  174  may be affixed to the object  12 , either to convert the projective surface to a metric surface, or if to further improve accuracy of three-dimensional reconstruction if already a metric surface. In some embodiments, two ground control points  174  or targets  76  may be used. Number and spacing of the ground control points  174  and/or targets may be determined based on setback of sensing system  14 , circumferential span of object  12 , parameters of camera(s) and/or the like. 
     In some embodiments, parameters of the digital imaging device(s)  32  may be unknown, and as such, scan of the object  12  may be too planar and/or flat such that photogrammetric three-dimensional construction may show errors related to distortion (e.g., bowl distortion). Such errors may be reduced by placing ground control points  174  and/or targets  76  within the field of view of the digital imaging device(s)  32 . While the resulting three-dimensional construction may be accurate, the model may include the actual three-dimensional representation of the ground control points  174  and/or targets  76 . In some embodiments, a rigid frame may be positioned on periphery of the object  12 . One or more patterns  172  may be marked on the rigid frame. The frame may be light enough to be portable and configured to be removable or attached to the object  12  or periphery of the object  12 . 
     In some embodiments, the photogrammetry targets  76  and/or ground control points  174  may be printed or machined on a rigid surface with dimensions similar to a credit card (e.g., 3.37 inches×2.125 inches) so as to be configured to fit within a wallet or purse, for example. 
     In some embodiments, the surface with ground control points  174  and/or targets  76  may be affixed to the object  12  (e.g., adhesive, magnet, and/or the like). For example,  FIG. 5C  illustrates a card marked with ground control points  176  is affixed to steel belts of a tire. In another example, the card is affixed to a sole of an athletic shoe as shown in  FIG. 5D . 
     In some embodiments, a rough orientation may be performed on the tire swath  70 . For example, an algorithm known as random sample consensus (RANSAC) may be used to find a best fit plane on the object  12  close to the XY plane (i.e., a best fit plane over the protrusions  22  (e.g., tread block)). This rough orientation may correct for large distortions. 
     Referring to  FIGS. 1 and 7 , a convex hull  80  for the tire swath  70  may be determined by the user system  26 . Algorithms for determining the convex hull  80  for the tire swath  70  are known and included in commercially available software packages, such as Visualization Tool Kit (VTK) manufactured by Kitware having a principal place of business in Clifton, N.Y. and Qhull provided by The Geometry Center of The University of Minnesota. The convex hull  80  models an outer boundary of the tire swath  70  in a manner that extends over the grooves  20 . The convex hull  80  may aid in determining depth of the grooves  20  of the tire swath  70 . Depth of the grooves  20  may provide a basic test of health of the object  12 . Generally, the convex hull  80  created for the tire swath  70  is the smallest convex set of the tire swath  70 . To that end, the convex hull  80  of the tire swath  70  would follow the surface  24  of the protrusions  22 . As such, depth of the grooves  20  within the tire swath  70  may be determined as a distance d between the convex hull  80  and the portion  82  of the tire swath  70  parallel to the tire swath  70  within the groove  20  as illustrated in  FIG. 8 .  FIG. 9  illustrates the determination of depth of the grooves  20  for the entire tire swath  70 . In some embodiments, the user system  26  may calculate and provide the user with a digital image illustrating depth of the grooves  20  for the tire swath  70  and/or the entire object  12 . The depth of the grooves  20  can be determined by calculating a difference between a three-dimensional location of a point on the convex hull  80  that is perpendicular to a point of the object  12  that is at the bottom of the groove  20 . By calculating multiple differences at various locations within the grooves  20  of the tire swath  70 , the depth of the grooves  20  can be determined, modeled and graphically depicted. In some embodiments, the user system  26  may calculate and provide the user an average depth for the tire swath  70  and/or the entire object  12 . The average depth can be calculated by calculating an average of the differences at various locations within the grooves  20  of the tire swath  70 . 
     Referring to  FIGS. 1, 10A and 10B , orientation of the tire swath  70  may further aid in diagnosing health of the object  12 . Non-tread related wear (i.e., objects  12  without tread) may need orientation of the object  12  so that wear patterns may be analyzed. For example, a brake rotor may be assessed for run out if the rotor is first oriented. Objects  12  having tread may also benefit from orientation for diagnostics and the like. Generally, orientation may be based on how the tire swath  70  is positioned during use of the object  12 . For example, orientation of the tire swath may be how the tire swath  70  would spin on the tire of the vehicle if the tire was properly aligned. It should be noted that some sensing systems  14  may be capable of providing information as to orientation of the entire three-dimensional model. For example, laser scanning systems (e.g., turntable/lab based and driveover systems) may be used to capture a full three-dimensional model, and as such, the orientation may be provided using an algorithm known as Principal Component Analysis, for example. In using a turn table system known with the art, the tire may be spun on a vertically or horizontally positioned wheel with the distance between the laser and tire being constant to enable and/or establish correct orientation of the three-dimensional model. Alternatively, if only the tire swath  70  is available, symmetry analysis may be used to facilitate orientation. Exemplary methods of orienting the tire swath  70  are discussed below. 
     In some embodiments, symmetry of the tread on the object  12  may be used to orient the tire swath  70 . Tire symmetry is further described in the paper by Gregory Jackson entitled,  Symmetry in Automobile Tires and the Left - Right Problem , University College (NSW), ADFA, Canberra, Australia 2600, which is hereby incorporated by reference in its entirety. Patterns of grooves  20 , for example, on each side of the tire may often be identical even if staggered circumferentially. Such patterns of grooves  20  may repeat circumferentially about the tire. Further, sidewalls of the tire may be symmetric. 
     Referring to  FIGS. 10A-10C , n some embodiments, the tire swath  70  may be oriented by determining symmetries associated with the tire swath  70 . In some embodiments, orientation of the tire swath  70  may be on a tire swath  70   a  of a baseline surface model (e.g., a tire with limited or no wear) as a newer tire may be more symmetrical than a tire with wear. Generally, the pattern of the tire swath  70   a  may be exploited, and in particular the 180 degree symmetry. The grooves  20  of the tire swath  70   a  may be isolated and analyzed as this portion of the tire swath  70   a  may generally be invariant. Landmarks of the grooves  20   a  may be used to orient the tire swath  70   a . For example, one or more center points C P  of the grooves  20   a  as shown in  FIG. 10A  may be used to establish a vertical landmark at a center of each groove  20   a . Such center points C P  may then be registered to corresponding grooves  20  of the tire swath  70 . Other landmarks may be used to orient the tire swath  70   a  including patterns of the grooves  20   a , patterns of protrusions  22   a , depth of grooves  20   a , width of grooves  20   a , direction of grooves  20   a  and/or the like. 
     The tire swaths  70  of tires with wear may then be registered to the tire swath  70   a  as illustrated in  FIG. 10B . Further, an ICP may be performed and a distance between the tire swath  70  and the tire swath  70   a  may be determined. Further, a threshold scan may be performed to further limit the distance D between the tire swath  70  and the tire swath  70   a  such that grooves  20   a  and grooves  20  may be substantially identical as shown in  FIG. 10C . In some embodiments, principle component analysis (PCA) may also be used to further orient the tire swath  70 . The resulting transformation may then be applied to the entire tire swath  70 . 
     In some embodiments, the tire swath  70  may be oriented using a bounding box  84  as shown in  FIG. 11A . Generally, the minimum oriented bounding box  84  may be determined and, using the bounding box  84  and principal component analysis, the tire swath  70  may be oriented along the X axis, Y axis and/or Z axis. 
     Referring to  FIG. 11A , the bounding box  84  may be configured about the tire swath  70  as shown. Generally, the bounding box  84  is a box for a point set(s) in N dimensions within which all of the points lie. The bounding box  84  may be the minimum box for a point set (S) in N dimensions having the smallest measure within which all the points lie. The bounding box  84 , once determined, may then be oriented to each axis (i.e., X-axis, Y-axis and/or Z-axis). In some embodiments, the bounding box  84  may be oriented to each axis using an algorithm known as principal component analysis to determine transformation T for aligning the bounding box  84  to the X-axis, Y-axis, and/or Z axis. For example,  FIGS. 11B-11E  illustrate the tire swath  70  being oriented to each of the X-axis (shown in  FIG. 11C ), the Y-axis (shown in  FIG. 11D ), and the Z-axis (shown in  FIG. 11E ). 
     Referring to  FIG. 12 , once aligned in the X, Y and Z axis, the tire swath  70  may then be circumferentially translated. In some embodiments, angular orientation may also be adjusted. Referring to  FIGS. 13A and 13B , to circumferentially translate the tire swath  70 , the tire wheel radius R TW  may be determined. Generally, tire wheel radius R TW  may be estimated using the radius of the wheel R W  and section height H S  of the tire as shown in EQS. 1 and 2 below. The tire aspect ratio (TAR) and the section width W S  of the tire may be known. For example, the tire aspect ratio (TAR) and the section width W S  may be provided by the manufacturer of the tire and branded on the tire as shown in  FIG. 13 .
 
 R   TW   =R   W   +H   S   (EQ. 1)
 
 H   S =TAR* W   S   (EQ. 2)
 
     In one example, the tire aspect ratio (TAR) may be 75 and the section width W S  may be 295 mm. The section height H S  may then be about 221.25 mm. The diameter of the wheel may be as 22.5 inches. As such the radius of the wheel is approximately 507 mm. The tire swath  70  may then be adjusted such that the circumferential radius of the tire is set at approximately 507 mm, and dimensions of the tire swath  70  may be adjusted to fit the tire as illustrated in  FIG. 14 . For example, the user system  26  may use a trial and error approach to fit the tire swath  70  and/or adjust the tire swath  70  such that the circumferential radius of the tire is set at approximately 507 mm. In some embodiments, a visual confirmation from a user may be provided to the user system  26  indicating that the adjustments to the tire swath  70  may be acceptable. In some embodiments, the user system  26  automatically (i.e., without human intervention) performs the adjustments to the tire swath  70  based on the determined and/or estimated circumferential radius of the tire. 
     Referring to  FIG. 15A , in some embodiments, the tire swath  70  may be further oriented using an Iterative Closest Point (ICP) algorithm. Generally, tire features (e.g., grooves  20 , protrusions  22 ) that are configured to change circumferentially may be identified on the surface of the tire. Initially, edges  90  of the protrusions  22  may be highlighted by filtering the tire swath  70  based on curvature as shown in  FIG. 15B . Knowing the depth for grooves  20 , the tire swath  70  may be further filtered such that markings found within grooves  20  may be removed as shown in  FIG. 15C . The tire swath  70  may be further filtered based on X normals to provide defined circumferential edges  92  as shown in  FIGS. 15D and 15E , wherein  FIG. 15E  is a magnified view of  FIG. 15D . The defined circumferential edges  92  may generally be clearly identifiable on tires without wear (i.e., new tires). The filtered tire swath  70  having defined circumferential edges  92  may be rotated to provide overlap of circumferential edges  92   a  of a baseline scan or secondary scan. Distance between the tire swath  70  and the baseline scan or secondary scan may be used to determine and/or adjust for correct alignment. Further, ICP may be performed to maximize overlap. Based on resulting transformation, orientation of the tire swath  70  may be fine-tuned. 
     Referring to  FIGS. 16A-16C , in some embodiments, tire pitch cycle (i.e., a repeating circumferential pattern on the tire swath  70 ) may be used to orient the tire swath  70 . Initially, the tire swath  70  may be filtered such that grooves  20  may be highlighted. For example, edges of grooves  20  may be filtered to highlight grooves  20  and one or more protrusions  22  as shown in  FIG. 16A . Protrusions  22  on the tire swath  70  may repeat circumferentially in a recognizable pattern at a certain cycle (i.e., tire pitch cycle). Referring to  FIG. 16B , the tire swath  70  may be rotated on common tire pitch cycles to determine a best fit for edges  90  of the tire swath  70  and edges  90   a  of a baseline scan or secondary scan. Common tire pitch cycles within the industry include 2, 3, 4, 5, 6, 10, 12 and 15 degree rotations.  FIG. 16B  illustrates a 3 degree rotation wherein edges  90  and  90   a  do not align. Similarly,  FIG. 16C  illustrates a 5 degree rotation wherein edges  90  and  90   a  do not align.  FIG. 16D , however, illustrates a 4 degree rotation wherein edges  90  and  90   a  do align. As such, the tire pitch cycle may be determined to be 4 degrees. 
     Referring to  FIGS. 17A and 17B , registering the tire swath  70  on a baseline tire swath  70   a  or secondary tire swath may allow for exploitation of tire geometry that may not be significantly altered with wear. For example, grooves  20  of the tire swath  70  or sidewalls may not significantly change with wear of the tire. Further, techniques such as ICP may be used to further tighten the registration.  FIG. 17A  illustrates the tire swath  70   a  of a relatively new tire having little to no wear.  FIG. 17B  illustrates the tire swath  70  of a secondary scan of the new tire after such tire has been used. As such, the tire swath  70  includes wear. 
     It should be noted that when examining tread of the tire swath  70 , there are a number of machine vision and imaging science techniques that may be used to provide the overall pattern of the tread, to compare the tread of the tire swath  70  to a baseline tire swath or secondary tire swath, and/or to provide quantitative metrics regarding the amount and characteristics of the pattern of the tire swath  70  as compared to the baseline tire swath or secondary tire swath. In one non-limiting example, when a photogrammetric method is used to generate a three-dimensional model of the tread, images  16  may be used to assist in the alignment analysis. First, edges may be detected. There are a number of algorithms that may detect the edges including, but not limited to ideal groove, gradient edge detection (e.g., Sobel 2D gradient with a Hough line transformation), and/or the like. When aligning edges, a simple correlation may use best fit for the tread patterns or the tire swath  70  and the baseline tire swath or secondary tire swath, and as such, deformation due to tread wear may be minimized. In some embodiments, invariant portions of the tire (e.g., the side walls, carcass, and bottom surface of the grooves  20 ) may be correlated and aligned. In this non-limiting example, tread edges may be compared by finding differences. Quantitative metrics may be found by finding an area between similar lines, and as such, the overall amount of deformation of the tread pattern, as well as angular measurements between two tread edges may be determined. 
     If photogrammetric images are not available, edges may be detected within the three-dimensional model using a methodology and/or algorithm such as Random Sample Consensus (RANSAC). This iterative method may eliminate outliers in order to find a set of data points that may be used in a simple least squares method in order to fit a line to the three-dimensional data points corresponding to the edges of the tread. Once edges have been identified, the same quantitative metrics described above may be generated using three-dimensional model space instead of the two-dimensional space. 
       FIGS. 23A-23L  illustrate an exemplary method for orienting, cleaning and scaling a tire swath  70 . In some embodiments, the IAD system  30  may be a Smartphone configured to provide diagnostics of the object  12 . In some embodiments, the IAD system  26  may facilitate capture of images  16  for relevant portions of the object  12  and provide post processing providing basic and advanced diagnostics (e.g., metrics including groove depth, etc). In some embodiments, data (spatial and tabular) may be stored in a cloud for later diagnostics. Generally, the IAD system  30  may filter and/or clean the tire swath  70  and rotate and/or translate the tire swath  70  to the orientation of the tire as seated on a vehicle. 
     Referring to  FIG. 23A , the IAD system  26  may capture images  16  of the object  12 . In some embodiments, the IAD system  26  may use Structure from Motion (SFM), a photogrammetric range imaging technique for estimating three-dimensional structures from two-dimensional image sequences. The IAD system  26  may be moved in a pre-determined path  210  (e.g., substantially straight path) across the object  12  (e.g., across tread of tire from bead to bead) to capture a suitable amount of images  16  to enable reconstruction of the object  12  (e.g., tire swath  70 ). 
     In some embodiments, a fiducial card may be used to achieve a metric projection as described in further detail herein. After processing, the fiducial card can be clipped from the resulting three-dimensional tire swath  70  as it is not part of the tire. Additional artifacts  77  may also be filtered out by keeping the largest connected component as illustrated in  FIG. 22 . 
     In some embodiments, initiation may begin by achieving a rough 180 degree rotational symmetry of the tire swath  70 . Depending on conditions of image capture of the tire swath  70  (e.g., images captures evenly and/or the like), the tire swath oriented to its center of mass may already achieve rough starting orientation. 
     The tire swath  70  may be oriented relative to the Z-axis (e.g., using best fit plane techniques). In some embodiments, the tire swath  70  may be roughly oriented in the Z-direction by searching for the flattest region of the tire (e.g., using plane fitting). Typically, the flattest region of the tire may be located near the center of the tread. 
     In some embodiments, the tire swath  70  may be roughly oriented in the Y direction (e.g., identifying best fit lines). Rough Y orientation may be achieved by methods including, but not limited to, edge thresholding (e.g., depth on circumferential grooves), identifying vertical line formed by boundaries of protrusions  22 , and/or the like. In another example, a series of profiles  360  of the sidewall and shoulder area may be determined using Z-cutting planes as illustrated in  FIG. 26A . The Y-orientation may be determined by repetitively reflecting the profiles at the Y origin, and correcting the Y orientation to minimize the distance between the original and reflected profile.  FIG. 26B  illustrates a profile of the unrotated tire swath  70  alongside its reflection.  FIG. 26C  illustrates the profile of the Y rotation corrected tire swath  70 . Other methods of achieving orientation are described herein. 
     Referring to  FIG. 26D , once the swath  70  is roughly oriented in the Y-axis and Z-axis, the swath  70  can be clipped by a bounding box  230  so that it is relatively symmetric in X, Y and Z. low quality data may be removed from the periphery of the tire swath  70 . In another example, as illustrated in  FIGS. 27A and 27B , the bounding box may be used both to achieve reasonable symmetry on the tire swath  70  and/or to remove extraneous artifacts (e.g., a fiducial card). 
     Once the tire swath  70  is roughly oriented and relatively symmetric,  FIGS. 23B to 23F  illustrate a method to achieve a robust orientation by exploiting symmetry of the tire carcass illustrated in  FIG. 23B  and  FIG. 23C .  FIG. 23D  illustrates the convex hull of the tire mesh trimmed to remove all faces and points except those at the top (i.e., the hull of the top surface may be extracted (CHTOP)). The resulting tire mesh may be rotated 180 degrees (R180SCHTOP) as illustrated in  FIG. 23E . Iterative closet point processing may be performed on the convex hull of the top of the surface (CHTOP) and target (R180CHTOP) registering the original hull to the rotated hull. Distances that are excessively large may be discarded and scale may be adjusted. Without loss of generality (as quaternions or Rodriquez angles may be used as an alternative to rotation matrices), a resultant transformation M (wherein M is applied to the original tire mesh to best fit to the rotated mesh) may be used to better orient the original tire swath  70  in (X, Y, Z) by (a) converting the rotation matrix R in M to Euler notation and separating the translation vector T from M; (b) dividing the resulting Euler angles (x/y/z) and the translation vector by 2; (c) converting the halved Euler angles to a rotation matrix R, and combining R and the modified/halved translation vector T back to a transformation matrix M 1 ; and (d) applying M 1  to the original tire mesh as illustrate d in  FIG. 23F . 
     Tire tread width refers to the width of the tire with tread. Tread width is a quantity tracked by tire manufacturers and third party dealers. In swath coordinates, tread width may be measured such as followed. Referring to  FIGS. 23G-23I  geometric boundaries of tread width may be determined by constructing a convex hull on the tire swath  70  and identifying boundaries B on either side of the tire based on steepest drop. Width of the tire swath  70  may be determined by clipping the tire swath between the boundaries B 1  and B 2  and determining width. A scale may then be determined between the width of the tread in swath coordinates and world coordinates. In the absence of known tread width, dimensions, it may be estimated as a fraction C of section width. Section width is always a known quantity as section width is branded on each tire. The fraction C may vary between approximately 0.75 and 0.85. 
     Occasionally, extraneous material (e.g., dirt, stones, vestiges of rubber molding) may be on the object  12  during a scan inducing error such as artificially increasing distance in determining groove depth. In some embodiments, an aggregate convex hull may be determined using multiple slices  220  as shown in  FIG. 23J ,  FIG. 23K  and  FIG. 23H . Referring to  FIG. 23K , by using the aggregate convex hull with multiple slices  220 , the effect of extraneous material may be localized to a cross section. As such, higher depth readings caused by the extraneous material may be removed. In some embodiments wherein the tire surface may not be convex (e.g., due to center wear), depth measurements of the individual grooves  20  may be determined by separating the grooves  20  from the remainder of the object  12  and form convex hulls on each individual groove  20  as illustrated in  FIG. 23L  Extraneous material outside of the groove  20  may thus be avoided. 
     In some embodiments, the tire swath  70  may be scaled by capturing at least one image  16  of a known object having known parameters by the IDA system  30 . For example, a known object with known parameters may include a penny or a credit card. 
     Referring to  FIG. 24A , in some embodiments, the tire swath  70  may be scaled by establishing section width, aspect ratio and/or wheel diameter. Establishing a scale based on section height may require capture of a larger tire swath  70  or exploitation of tire symmetry, for example. In one example, a scan may be initiated towards the bottom of the outside sidewall of the tire and terminate slightly past the inner shoulder of the tire. A bounding box  230  of the oriented and unscaled tire swath  70  may be used to determine section width, and thus create a swath coordinate to world coordinate scale. It should be noted that three-dimensional extraction of the tire swath that may include section width boundaries may entail capture of a plurality of images across the tire and may be more ergonomically challenging if the tire is mounted on the vehicle. As another alternative, tire diameter may also be used to create a swath coordinate to world coordinate scale. 
     Radius of the tire may be determined directly or indirectly from information including section width, aspect ratio and wheel diameter branded on the sidewall of the tire. For example, section height is equal to section width multiplied by aspect ratio and the radius of the tire may be calculated as the sum of the section height of the tire and half of the diameter of the wheel. To estimate the radius of the tire swath  70 , a best fit three-dimensional circle may be constructed from a slice down the middle of the tire swath  70  as illustrated in  FIG. 24B . In some embodiments, the slice may be thresholded by depth of the grooves  20  to isolate points near protrusions  22  and remove outliers. The slice  350  may then be fit to the best fit circle associated with point in  FIG. 24C  and a scale may be constructed by using the calculated radius in swath coordinates and the known radius in world coordinates. It should be noted that the accuracy of the estimated radius may depend in part on the circumferential span of the tire swath  70 . For example, in  FIG. 24B , a sequence of images was captured across the tread and then another sequence of photos was captured down the middle. The top third (approximately) of the tire swath  70 , including shoulders on each side, may be used to orient the tire swath  70  (as described herein) for determination of radius. 
     The tire swath  70  may be registered (e.g., superimposed) on one or more tire swaths  70   a  obtained from the same and/or similar tires to identify alterations in grooves  20  and  20   a  and/or protrusions  22  and  22   a  between the swaths  70  and  70   a . Generally, analysis may be on the grooves  20  and  20   a  as grooves  20  on the tire having wear may not be altered significantly with wear and thus distinguishable within scans. Further, registering the tire swath  70  may include exploitation of geometry of the object  12  that undergoes minimal change or no change during wear of the object  12 . For example, if the object  12  is a tire, then grooves  20  of the tire and sidewalls may be used to aid in registering the tire swath  70  to tire swath  70   a . The tire swath  70   a  may be a new tire or used tire. For example, the tire swath  70   a  may be a used tire and evaluation of the tire swath  70  as compared to the tire swath  70   a  may provide data regarding change in wear over a pre-determined time period (e.g., 2 months). 
     In some embodiments, the scans may be thresholded by distance so as to limit the view to the grooves  20   a  and  20 . For example, by thresholding each groove  20   a  of the tire without wear the groove  20   a  may be matched with the depth of the corresponding groove  20  of the tire having wear as shown in  FIGS. 18A and 18B . The tire swath  70   a  may be altered such that each groove  20   a  is worn down to approximately the size of the groove  20 . Determination of such approximation may be based on approximate distance of wear to obtain groove  20   c  illustrated in  FIG. 18B . It should be noted that the size and/or shape of groove  20   c  may not be exactly the size/shape of groove  20 . Thresholding may be limited to the average depth of grooves  20  for the tire with wear. Grooves  20  of the tire with wear may then be translated down in the Z axis based on the difference between grooves  20  and grooves  20   a  such that the grooves  20  and  20   c  may be registered as shown in  FIGS. 18B and 18C . In some embodiments, ICP (i.e., weighting ICP) may be performed on the grooves  20  and  20   a  providing a transformation T. As such, weighting may provide substantially equal weight latitudinally across the tire swath  70  to the different grooves  20  such that shallow grooves may have as significant an impact on the resulting transformation as deep grooves. The tire swath  70  may be transformed based on the transformation T as shown in  FIG. 18D . In some embodiments, rigid body transformation may be performed. In some embodiments, non-rigid body transformation may be performed. 
     Referring to  FIGS. 1 and 18A-18E , in some embodiments, the pattern of the grooves  20  and protrusions  22  may be complicated (e.g., more than simple circumferential groove of same dimension). For complicated patterns, the tire swath  70  may be rotated about the tire swath  70   a  to locate a match of the pattern between the tire swath  70  and the tire swath  70   a . In this example, the tire swath  70   a  may contain at least one entire pattern (e.g., tread cycle). Further, a map of the tire swath  70  and/or tire swath  70   a  may be determined using one or more metrics. Metrics may include, but are not limited to, depth of grooves  20  (such as described and determined herein), direction of grooves  20 , width of grooves  20 , and/or the like. For example, a map may be determined using width of grooves  20  with an assumption that width of the groove  20  may diminish as depth of the groove  20  decreases. 
     Diagnosis of wear of the object  12  may be determined using the convex hull analysis, orientation analysis, registration analysis as described in further detail herein. 
     In some embodiments, depth of the grooves  20  provided by the convex hull analysis may provide one or more action items related to the object  12 . For example, depth of the grooves  20  determined by the convex hull analysis may be averaged and the average may be compared against one or more databases having one or more thresholds for tire replacement recommendation. In another example, depth of the grooves  20  may be determined by the convex hull analysis and each measurement compared against one or more databases having one or more thresholds. New tires may typically come with 10/32″ or 11/32″ tread depths. In some embodiments, the threshold for tire replacement recommendation may be based on the U.S. Department of Transportation recommendation of replacement of tires when they read 2/32″. In some embodiments, the threshold for tire replacement recommendation may be based on state law. For example, the one or more database may include one or more states within the United States and the associated legal threshold for tread depth. 
     In some embodiments, once the tire swath  70  is oriented, one or more diagnosis related to wear of the tread may be determined. For example, heel toe wear and camber wear may be determined subsequent to orientation of the tire swath  70 . Generally, for each of the heel toe wear and camber wear, the tire swath  70  may be compared to known patterns of wear related to heel toe wear and camber wear as described in further detail below. 
       FIG. 19A  illustrates the tire swath  70 . A vertical line L is provided extending from the center of the wheel. As the surface of the tire is reflective of alignment issues, an evenly worn surface may indicate that the vehicle is correctly aligned.  FIG. 19B  illustrates the effects of camber wear on the tire swath  70 . As the tire is tilted, a portion of the tire may be raised off of the ground while the remaining portion may be heavily worn according to the camber angle Θ C  of the tilt. Generally, for camber diagnostics, the relative angle of the protrusions  22  between the tire swath  70  and the tire swath  70   a  may be evaluated. The baseline tire swath  70   a  may be registered to the tire swath  70  based on the grooves  20  as described in detail herein. For example, in  FIG. 19B , the baseline tire swath  70   a  and the tire swath  70  (e.g., worn tire) may be oriented and registered as described in further detail herein. Once oriented and registered, the baseline tire swath  70   a  may have a camber angle Θ C  of 0 degrees even though surface of the protrusion  22  may be slightly angled. The difference between the angle of the tire swath  70   a  and the tire swath  70  is the camber angle Θ C . 
     Protrusions  22  may develop excessive wear on the edge that touches the road last, known as “heel and toe” wear. An action item, such as changing direction of rotation (e.g., rotating tires) may counteract this pattern. It should be noted that currently industry practice does not provide measurement for heel toe wear. As such, it is contemplated herein, a database may be provided and determined for one or more reference points (e.g., thresholds) for “heel and toe” wear. For example, using system and techniques provided herein, one or more database may be determined having tire type (e.g., manufacturer, model, pattern) and associated measurements related to heel and toe wear as described in detail herein. Additionally, one or more thresholds may be determined to provide one or more action items based on the configured database. For example, by analyzing the configured database, a threshold for one or more measurements may include an action item prompting a user to replace one or more tires. 
       FIG. 20A  illustrates effects of heel and toe wear on protrusions  22  and how rotation of tires may aid in counteracting the wear. Referring to  FIG. 20B , to determine heel and toe wear, a line  103  may be extended from a first edge  104  of a first protrusion  22   d  to a second edge  106  of a second protrusion  22   e . The slope S of the line  103  may be determined. Additionally, a line  108  may be extended from the first edge  104  to an expected edge  110  of the second protrusions  22   e . The angle formed at the intersection of lines  103  and  108  may provide a heel top angle Θ HT . A pre-determined threshold may be determined for the heel top angle Θ HT  for one or more action items. For example, a pre-determined threshold may be determined for the heel top angle Θ HT  for recommendation of the action item of a tire rotation. 
     In some embodiments, the slope S may be identified circumferentially. For each tire, for example, depth may be determined on multiple sides of the protrusion  22 . For example, depth may be determined on the side of the protrusion  22  that leads (i.e., touches ground first) and side of the protrusion  22  that trails. The Heel/Toe Ratio may then be determined using EQ. 3:
 
Heel/Toe Ratio=Average Leading Edge Depth/Trailing Edge Depth  (EQ. 3)
 
A pre-determined threshold may be determined for Heel/Toe Ratio for one or more action items. As such, tires may be rotated when the heel toe ratios reaches a pre-determined threshold, for example.
 
     Orientation and registration of the tire swath  70  on a baseline tire swath  70   a  may provide an indication and diagnosis for toe wear.  FIGS. 21A-21C  illustrate toe wear of the tire swath  70 .  FIG. 21A  illustrates response of the grooves  20   b - 20   f  to different types of wear. The direction of the vehicle is indicated by line  100 . Without loss of generality, the driver side tire is herein described. Generally, groove  20   b  illustrate no wear (i.e., substantially perfect alignment). The groove  20   c  illustrates a stationary vehicle and shows a slight rotation in the XY plane. The groove  20   d  illustrates a moving vehicle. The wheel (and thus the groove  20 ) may be rotated slightly in both the XY and XZ planes. Wearing effect of toe wear may not yet be visible. Referring to  FIGS. 21A and 21B , the groove  20   e  illustrates tread wear after miles. In  FIG. 21B , the top figure illustrates later effects of wear while the bottom figure illustrates early effects of wear. Referring again to  FIG. 20A , the groove  20   f  illustrates registering the groove  20   e  to the groove  20   b . The groove  20   e  may indicate the orientation and magnitude of toe (i.e., negative amount of XY rotation required to register the groove  20   b ). 
       FIG. 21C  illustrates a planar view of the groove  20   e  registered to the groove  20   b . The arrow  102  may follow the boundary between the groove  20   e  and the groove  20   b . The direction of the arrow  102  may correspond to the amount of toe. 
     In some embodiments, a tire may be characterized as a series of three-dimensional cylinders, symmetric across the X centerline. Certain properties of the oriented tire swath  70  may be exploited to confirm orientation and/or improve orientation (of the un-oriented tire swath  70 ) and/or to construct a reliable scale converting the tire swath  70  to a measure surface. These properties may include: center of the tire having the greatest circumference (and a known circumference for purpose of determining a scale); circumference of cylinders at roughly the same X displacement from the centerline may be similar in magnitude; and, assuming one of the three-dimensional circle fitting algorithms (e.g., minimizing Sampson distance, least squares fit, eigenspace decomposition and/or the like) is used to find circumference at a specified X displacement (i.e., latitudinal position) based on a cross section of points from the tire swath  70  captured at X. Measurements from a tire swath that is un-oriented may correspond to an ellipse and may have greater errors (and more outliers) than oriented tire swath. 
       FIGS. 25A-25D  illustrate an exemplary method of orienting the tire swath  70  using the cylindrical nature of the oriented swath.  FIG. 26A  illustrates the oriented tire swath  70  includes a sliced center  330  and displacement slices  332  and  334  at a first side and a second side of the center, respectively.  FIG. 25B  illustrates the center slice  330  and the displacements slices  332  and  334 . The center slice  330  has the largest radius. The radius of the displacement slices  332  and  334  are nearly identical.  FIG. 25C  illustrates the tire swath  70  unoriented. The unoriented tire swath  70  includes a sliced center  336  and displacement slices  338  and  340 . The slices of the tire swath  70  that is unoriented includes slices that may not be circular in nature (i.e., there may be significant outliers using best fit circle). To that end the sliced center  336  may deviate in circumference as compared to the displacement slices  338  and  340  as shown in  FIG. 25D . 
     Using the system and methods as described herein, one or more tire profiles may be determined. The tire profile may define one or more metrics for the tire including, but not limited to, squareness (underinflation), roundness (overinflation) and/or the like. By examining and comparing the defined tire profile using secondary scans, one or more diagnosis may be determined and one or more action items may be recommended. Further prior history (e.g., prior scans including the baseline scans and secondary scans) may be analyzed (e.g., in succession) and used to diagnosis and/or recommend one or more action items. 
     Referring to  FIG. 1 , once a diagnosis is made for the wear of the tread of the object  12 , one or more reports may be provided to the user system  26 . Reports may be one or more communications to the user system  26  identifying one or more actions based on the one or more diagnosis. Communications may be by text, e-mail, notification, and/or the like.