Patent Publication Number: US-2021192715-A1

Title: Automated grains inspection

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is a continuation-in-part of co-pending U.S. patent application Ser. No. 16/400,614, filed May 1, 2019, incorporated herein by reference in its entirety. 
    
    
     TECHNICAL FIELD 
     The present disclosed subject matter relates to automated inspection apparatus. More particularly, the present disclosed subject matter relates to managing and controlling system for a user to interface with inspecting apparatus. 
     BACKGROUND 
     Automated inspection is a process of inspecting small solid materials, typically hard, as a part of controlling the quality of the particles in a production line. Optionally, the inspecting process can have a sorting process of the materials. Commercially available inspecting machines use optical sensors and image processing for determining impurities, change in geometry, and color. Typically, the inspecting machines compare the solid particles objects to user-defined baseline thresholds for qualifying the material into production/shipment or failing it. 
     Old fashion manual inspecting and/or sorting is subjective, unreliable and inconsistent, whereas optical sorting improves the overall product quality, maximize throughput, increase yields and reduces manual labor costs. 
     Inspecting machines can be used for products such as plastic grains, metal, or glass grains, or the like as well as food material such as beans, spices, nuts, grains, rice, vegetables and fruits. 
     BRIEF SUMMARY 
     Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosed subject matter belongs. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present disclosed subject matter, suitable methods and materials are described below. In case of conflict, the specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and not intended to be limiting. 
     It is therefore provided in accordance with the present subject matter, a management and control system for a user to interface with an inspecting apparatus having at least one digital optical instrument, the management and control system comprising:
         a processor configured to receive images from the at least one digital optical instrument, analyze the images, and transmit instructions to the inspecting apparatus;   a display configured to display analysis of the images wherein the user is capable of interfacing and providing instructions to the inspecting apparatus based on the analysis of the images, wherein the display simultaneously displays histograms and thumbnail-image generated in the processor based on the images.       

     In accordance with another preferred embodiment, the inspecting and sorting apparatus is configured to inspect items selected from a group of items consisting of beans, spices, nuts, grains, rice, vegetables, fruits, plastic grains, metal grains, glass grains, pharmaceutical pills. 
     In accordance with another preferred embodiment, the at least one digital optical instrument is selected from a group of optical instruments consisting of X-ray detector, magnetic resonance imaging (MRI) device, computed tomography (CT) scanner, 3D data scanner, camera, optical sensor. 
     In accordance with another preferred embodiment, the display is selected from a group of displays consisting of monitor, screen, electroluminescent (ELD) display device, liquid crystal display (LCD) device, light-emitting diode (LED) device, plasma (PDP) display, electronic hand-held device such as a tablet, a smartphone device. 
     In accordance with another preferred embodiment, the instructions are selected from a group of instructions consisting of sorting the items, enable ejection of items, disable ejection of items, generate report, setting discrimination level, diverting the items, setting thresholds to generate alarms, defining data set for automatic prediction and alarming, defining setpoint for production line control. 
     In accordance with another preferred embodiment, the management system further comprises a memory unit communicating with said processor wherein the memory unit is configured to retain information selected from a group of information consisting of the images, reference images, a plurality of profiles of the items, system settings, system reports, image analysis, reference profiles comprising thresholds for different types of items, statistical analysis associated with reference profiles. 
     In accordance with another preferred embodiment, the display graphically displays graphs generated in the processor based on the images. 
     In accordance with another preferred embodiment, the inspecting apparatus is incorporated within a production line. 
     It is also provided in accordance with another preferred embodiment, a method of managing and controlling an inspecting apparatus of items, the method comprising:
         capturing images of the items inspected by at least one digital optical instrument of the inspecting apparatus;   receiving by a processor the images from the at least one digital optical instrument;   analyzing the images by the processor so as to have an analysis of the items;   displaying the analysis on a display wherein while simultaneously displaying histogram representations and thumbnail images; and   receiving by the inspecting apparatus instructions interfaced by a user.       

     In accordance with another preferred embodiment, the analyzing the images comprises determining criteria of each item in the image, wherein the criteria are selected from the group consisting of impurities, change in geometry, color of the items, dark specks, dark gels, dark and bright contaminations, foreign material, discoloration, cross-contamination, color measurement and color shift, size deviation, shape irregularities, agglomeration, transparency, gloss of the items. 
     In accordance with another preferred embodiment, the method further comprising generating histogram representations of dimensions and criteria of the items. 
     In accordance with another preferred embodiment, the method further comprising setting thresholds based on the histogram representations, thumbnail images, and graphs. 
     In accordance with another preferred embodiment, the instructions interfaced by a user comprises instructions selected from a group of instructions consisting of sorting the items, enable ejection of items, disable ejection of items, generate report, setting discrimination level, diverting the items, setting thresholds to generate alarms, defining data set for automatic prediction and alarming, defining setpoint for production line control. 
     In accordance with another preferred embodiment, an interface interfacing is provided between a user and an inspecting apparatus so as to allow the user to simultaneously receive visual and statistical information from the inspecting apparatus and provide instructions to the inspecting apparatus, the interface comprising:
         a processor configured to receive images from the inspecting apparatus, display at least a portion of the images, perform statistical analysis based on the images and form distribution histograms;   a display configured to simultaneously display at least the portion of the images and the distribution histograms; and   input device for the user to provide instructions to the processor and interface with the inspecting and sorting apparatus.
 
In accordance with another preferred embodiment, the at least portion of the images and the distribution histograms correspond to one another.
       

    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Some embodiments of the disclosed subject matter described, by way of example only, with reference to the accompanying drawings. With specific reference now to the drawings in detail, it is stressed that the particulars shown are by way of example and for purposes of illustrative discussion of the preferred embodiments of the present disclosed subject matter only, and are presented in the cause of providing what is believed to be the most useful and readily understood description of the principles and conceptual aspects of the disclosed subject matter. In this regard, no attempt is made to show structural details of the disclosed subject matter in more detail than is necessary for a fundamental understanding of the disclosed subject matter, the description taken with the drawings making apparent to those skilled in the art how the several forms of the disclosed subject matter may be embodied in practice. 
       In the drawings: 
         FIG. 1  illustrates an automated grains inspection apparatus (AIA), in accordance with some exemplary embodiments of the disclosed subject matter; 
         FIG. 2A  illustrates a front view of the automated grains inspection apparatus, in accordance with some exemplary embodiments of the disclosed subject matter; 
         FIG. 2B  illustrates a front view of the automated grains inspection apparatus of  FIG. 1  comprising a display device, in accordance with some exemplary embodiments of the disclosed subject matter; 
         FIG. 2C  illustrates a front view of another sorting system comprising a display device, in accordance with some exemplary embodiments of the disclosed subject matter; 
         FIG. 2D  illustrates a front view of yet another sorting system comprising a display device, in accordance with some exemplary embodiments of the disclosed subject matter; 
         FIG. 3  shows a cross-sectional side view of the automated grains inspection apparatus, in accordance with some exemplary embodiments of the disclosed subject matter; 
         FIG. 4  shows a top view of the automated grains inspection apparatus, in accordance with some exemplary embodiments of the disclosed subject matter; 
         FIG. 5  is a screenshot of a video frame showing grains in inspection process, in accordance with some exemplary embodiments of the disclosed subject matter; 
         FIG. 6  shows a block diagram of a grains inspection system, in accordance with some exemplary embodiments of the disclosed subject matter; 
         FIG. 7  shows a flowchart diagram of a method for grains inspection, in accordance with some exemplary embodiments of the disclosed subject matter; 
         FIG. 8  shows a workstation screenshot depicting an outcome report, in accordance with some exemplary embodiments of the disclosed subject matter; 
         FIG. 9  shows the workstation screenshot depicting another outcome report, in accordance with some exemplary embodiments of the disclosed subject matter; 
         FIG. 10  shows the workstation screenshot depicting yet another outcome report, in accordance with some exemplary embodiments of the disclosed subject matter; 
         FIG. 11  shows a workstation screenshot depicting an outcome report, in accordance with some exemplary embodiments of the disclosed subject matter; 
         FIG. 12  shows a workstation screenshot depicting an outcome report in trend view, in accordance with some exemplary embodiments of the disclosed subject matter; 
         FIG. 13  shows a workstation screenshot depicting an outcome report in thumbnail view, in accordance with another embodiment of the disclosed subject matter; 
         FIGS. 14A and 14B  show a workstation screenshot depicting an outcome report of dark defects inspection in thumbnail view, in accordance with some exemplary embodiments of the disclosed subject matter; 
         FIGS. 15A and 15B  show a workstation screenshot depicting an outcome report of size monitoring inspection in thumbnail view, in accordance with some exemplary embodiments of the disclosed subject matter; and 
         FIG. 16  shows a workstation screenshot depicting an outcome report of yellowness inspection in thumbnail view, in accordance with some exemplary embodiments of the disclosed subject matter. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     Before explaining at least one embodiment of the disclosed subject matter in detail, it is to be understood that the disclosed subject matter is not limited in its application to the details of construction and the arrangement of the components set forth in the following description or illustrated in the drawings. The disclosed subject matter is capable of other embodiments or of being practiced or carried out in various ways. 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. The drawings are generally not to scale. For clarity, non-essential elements were omitted from some of the drawings. 
     The terms “comprises”, “comprising”, “includes”, “including”, and “having” together with their conjugates mean “including but not limited to”. The term “consisting of” has the same meaning as “including and limited to”. 
     The term “consisting essentially of” means that the composition, method or structure may include additional ingredients, steps, and/or parts, but only if the additional ingredients, steps and/or parts do not materially alter the basic and novel characteristics of the claimed composition, method or structure. 
     As used herein, the singular form “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise. For example, the term “a compound” or “at least one compound” may include a plurality of compounds, including mixtures thereof. 
     Throughout this application, various embodiments of this disclosed subject matter may be presented in a range format. It should be understood that the description in range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the disclosed subject matter. Accordingly, the description of a range should be considered to have specifically disclosed all the possible sub-ranges as well as individual numerical values within that range. 
     It is appreciated that certain features of the disclosed subject matter, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the disclosed subject matter, which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable sub-combination or as suitable in any other described embodiment of the disclosed subject matter. Certain features described in the context of various embodiments are not to be considered essential features of those embodiments, unless the embodiment is inoperative without those elements. 
     Referring now to  FIG. 1  showing an automated grains inspection apparatus (AIA), in accordance with some exemplary embodiments of the disclosed subject matter. The AIA  100  is an apparatus configure to run a quality control process of inspecting solid material in a production line. In some exemplary embodiments, AIA  100  can be adapted to inspect and sort the material according to criteria, such as color, size, shape, structural properties and any combination thereof, or the like. The material sorted by AIA  100  is a plurality of discrete items, such as for example beans, spices, nuts, grains, rice, vegetables, fruits, plastic grains, metal grains, glass grains, pharmaceutical pills, and any combination thereof, or the like. 
     For the sake of simplicity, the present disclosure shall refer hereinafter to the material that is sorted by the AIA  100  as “grains” or “items”. 
     In some exemplary embodiments, the AIA  100  can be used in-line a production-line; off-line the production-line; in-parallel to the production-line; and any combination thereof. In the in-line exemplary embodiment, all the grains to be consumed in production first enters the AIA  100 , for inspecting, through an inlet, and preferably an inlet funnel  201  and proceed to the production-line from outlet  209 , where the grains are discharged. In the off-line exemplary embodiment, all or portion of the grains may be tested after being introduced to the production line. In the in-parallel exemplary embodiment, a portion of the material to be consumed in production enters the AIA  100 , for inspecting or sorting, through inlet funnel  201  and proceed to the production-line from outlet  209 . 
     Referring now to  FIG. 2A  showing a front view of the automated grains inspection apparatus, in accordance with some exemplary embodiments of the disclosed subject matter. AIA  100  comprises a housing  200  having an inspection zone, inlet funnel  201 , outlet  209 , second outlet  212  and sorting mechanism  213 . In some exemplary embodiments, inlet funnel  201  is interfacing between housing  200  and feeding tube or a hopper (not shown), which enables pouring grains into the AIA  100 . Housing  200  also incorporates feeder mechanism  202 , slot feeder  204 , background surface and preferably a first background surface  205 , a second background surface  206 , and a camera  207 . 
     In some exemplary embodiments, slot feeder  204  is adapted to receive grains from inlet funnel  201  and release them in line formation into the inspection zone of the housing, where the line thickness is substantially and preferably, but not necessarily equivalent to a thickness of a single grain. In that way, the slot feeder  204  acts as a buffer that collects grains and align them in a single line formation, across the housing  200 , so that they fall as curtainlike through the housing and through an inspection zone in which the grains are being imaged. In some exemplary embodiments, the feeder mechanism  202  can be used for adjusting the line thickness of an outlet (not shown) of the slot feeder  204  to a thickness of a single grain, or any other suitable thickness. In some exemplary embodiments, the first background surface  205  and the second background surface  206  may each constitutes a different background for images taken by camera  207 . It should be noted that camera  207 , situated on camera compartment  210 , faces (looking at) the curtainlike released grains and backgrounds  205  and  206  that are situated behind the curtainlike falling grains. 
     It should be also noted that a plurality of cameras can be used. One or more of the plurality of cameras can be positioned opposite the camera depicted in  FIG. 2A . In this way, the oppositely positioned camera captures images from the other side of the grains. The oppositely positioned camera can be provided with an independent illumination system and set of backgrounds. This double functioning apparatus enables capturing images for full inspection of the grains. 
     In some other exemplary embodiments, the grains can slide in a curtainlike structure on a surface that is inclined beneath the slot feeder, wherein the surface can be the background surface as an example. This optional structure can decrease the velocity of the grains when they pass through the inspection zone so as to enhance the quality of the image that will be captured by the camera. Generally, and in this case particularly, the slot in the slot feeder can be wider or a feeder can be used that has no slot and the grains pass through a feeder having another opening profile. 
     In some exemplary embodiments, upon detecting grains that fails (unqualified) quality control inspection, the sorting mechanism  213  can be configured to deflect unqualified grains from outlet  209  to second outlet  212 . It is provided in accordance with one aspect of the present subject matter a control system for a user to interface with an inspecting apparatus having at least one digital optical instrument, the control system comprising:
         a processor configured to receive images from the at least one digital optical instrument, analyze the images, and transmit instructions to the inspecting apparatus; and   a display configured to display analysis of the images wherein the user is capable of interfacing and providing instructions to the inspecting apparatus based on the analysis of the images.       

     It is also provided in accordance with yet another aspect of the present subject matter, an interface interfacing between a user and an inspecting apparatus so as to allow the user to simultaneously receive visual and statistical information from the inspecting apparatus and provide instructions to the inspecting apparatus, the interface comprising:
         a processor configured to receive images from the inspecting apparatus, display at least a portion of the images, perform statistical analysis based on the images and form distribution histograms;   a display configured to simultaneously display the at least a portion of the images and the distribution histograms; and   input device for the user to provide instructions to the processor and interface with the inspecting apparatus.       

     Referring now to  FIG. 2B  illustrating a front view of the automated grains inspection apparatus of  FIG. 2  comprising a display device, in accordance with some exemplary embodiments of the disclosed subject matter. In this embodiment, the AIA  100  further comprises a display device  220  such as a screen capable of displaying information. Display device  220  can be, for example, Electroluminescent (ELD) display device, Liquid crystal display (LCD) device, Light-emitting diode (LED) device, Plasma (PDP) display, a combination thereof or the like. The terms “display device” and “screen” are used for substantially the same feature and therefore, the terms can be interchanged. Screen  220  can be either connected to AIA  100  by wires or wirelessly. In some embodiments, screen  220  can be a computer monitor. In another embodiment, screen  220  can be on a remote device, such as an electronic hand-held device, for example a tablet. In yet another embodiment, screen  220  can be a smartphone device. 
     The information displayed on screen  220  can be either visual or tactile. Preferably, the information will be presented using graphical user interface (GUI). GUI is a form of user interface that allows users to interact with electronic devices through graphical icons and audio indicator such as primary notation, instead of text-based user interfaces, typed command labels or text navigation. The information is received from camera  207 , or from any other digital optical instrument such as X-ray detector, magnetic resonance imaging (MRI) device, computed tomography (CT) scanner, 3D data scanner and the like. Optionally, information can be retrieved from more than one digital optical instrument. The screen  220  displays histograms as will be elaborated hereinafter. The user interfaces with the AIA through an input device  221 . The input device can be from a group of devices such as keyboard, mouse, video, touch screen, etc. 
     Referring now to  FIG. 2C  illustrating a front view of another sorting system comprising a display device, in accordance with some exemplary embodiments of the disclosed subject matter. Sorting system  250  is operated to perform a quality control process of inspecting solid material in a production line. Sorting system  250  comprises material feed  251  connected to transport system  252 . Transport system  252  is attached to X-ray inspection component  253  that is followed by at least one optical inspection component  254 . Additional optical inspection component  258  and color camera  259  can be used to inspect the items. Sorting unit  255  sorts the inspected items, and separates them into rejected materials reservoir  256  and clean materials reservoir  257 . Screen  220  is attached to sorting unit  250 , displaying visual information related to inspection of items as will be discussed hereinafter. 
     Referring now to  FIG. 2D  illustrating a front view of a yet another sorting system comprising a display device, in accordance with some exemplary embodiments of the disclosed subject matter. Sorting system  270  is operated to perform a quality control process of inspecting and sorting solid material in a production line. Sorting system  270  comprises pre-hopper  271  connected to product feed  272 . Product feed  272  is attached to transport system  273  that moves the items into the inspection area. Inspection area comprises a charge-coupled device (CCD)  274  and fluorescent lamps  275 . Ejection nuzzle  276  ejects the inspected items that are rejected into reservoir  278 . Items that were not rejected are moved by transform system  273  to second inspection area. Second inspection area comprises a charge-coupled device (CCD)  274  and fluorescent lamps  275 . Ejection nuzzle  276  ejects the inspected items that are rejected into reservoir  278 . Items that were not rejected are ejected into reservoir  278 . Screen  220  is attached to sorting unit  270 , displaying visual information of histograms bearing visual information and statistical information related to inspection of items such as distribution of the items of specific type or size, as will be discussed hereinafter. 
     Referring now to  FIG. 3  illustrating a cross-sectional side view of the automated grains inspection apparatus (AIA), in accordance with some exemplary embodiments of the disclosed subject matter. Slot feeder  204  comprises mainly of two panels ( 204   a  and  204   b ) facing each other, however each of which is tilted away from the vertical axis of the AIA  100 . It can be appreciated from cross-sectional side view that slot feeder  204  has a trapezoid shape, in which the top base of the trapezoid is wide open as opposed to the narrow base (labeled “S” for slot), which can be adjusted by feeder mechanism  202 . In some exemplary embodiments, the feeder mechanism  202  can adjust slot  211  of slot feeder  204  to a span that correspond to typical thickness of a type of grain under inspection. 
     It will be noted that grains poured to inlet funnel  201  ingress slot feeder  204 , via the so called “top base of the trapezoid” and egress the slot feeder, in curtainlike formation, into outlet  209  while crossing the field of view (FOV) of camera  207 . In some exemplary embodiments, the span of slot  211  can be manually adjusted by means of feeder mechanism  202 . For example, handle, lever, screw bolt, and any combination thereof, or any commercially available mechanical means. Additionally, or alternatively, feeder mechanism  202  can be configured to be automatically adjusting the span of slot  211 , by means of: electrical/pneumatic motor, actuators, and any combination thereof, or the like. In some exemplary embodiments, the automatic adjustment of the feeder mechanism  202  can be controlled by a controller of the present disclosure (to be described in detail further below). 
     In some exemplary embodiments, sorting mechanism  213  can be comprised of mechanism types, such as deflection; flap removal; pressurized-air removal, diverter valve, and any combination thereof, or the like. 
     Both flap and pressurized-air removal can be utilized for rejecting a relatively small number of grains that fail the quality control. In some exemplary embodiments, upon detection of unqualified grain (to be described in detail further below) a small number of grains are removed from the production line by either a flap type or pressurized-air. It should be noted that, this removal either by the flap or by pressurized-air may be primarily, however not necessarily, used in an in-line and in-parallel production-line configurations. It should also be noted that, this discarding (removing) process may be repetitive as long as unqualified grains are detected. 
     In some exemplary embodiments, the flap removal type may be based, for example, a piece of a flat shelf hinged on one side, that covers an opening. Upon activation, the flap opens to enable a predetermine number of grains to be discarded. 
     In some exemplary embodiments, the pressurized-air removal type can be based on a commercially available air nozzle that blasts away, upon activation, a number of grains. The approximate amount/number of grains to be discarded can be controlled by adjusting the blast duration and diameter of the air jet. 
     In some exemplary embodiments, a deflection sorting mechanism may be primarily, however not necessarily, utilized in an off-line the production-line configuration. The deflection mechanism type may be based on a hinged door that operates as a selector allowing grains to outlet  209 , i.e., to production line, or deflect the grains to second outlet  212 . Typically, activation deflection allows relatively large amount of grains to be discarded, i.e., second outlet  212 , opens to enable a predetermine number of grains to be discarded. 
     In some exemplary embodiments of the disclosed subject matter, the sorting mechanism  213 , such as the types listed above may utilize solenoids, motors, actuators pneumatic components, and any combination thereof, or the like for implementing any or all the sorting mechanism types. 
     Among other components,  FIG. 3  depicts the side view of camera  207 , the first background surface  205 , the second background surface  206  and at least one background illumination  214 . In some exemplary embodiments, camera  207  may be situated in camera assembly  210  that enables sliding the camera forward and backward, i.e., toward and away from background surfaces  205  and  206 , so that the camera&#39;s FOV shall cover an area containing both backgrounds. The sliding of camera  207  may be done by means of sliding mechanism  215  in order to adjust the distance between a focal point of the camera and the area covering the background, hereinafter region of interest (ROI). In some exemplary embodiments, sliding mechanism  215  may be controlled either manually and or automatically by means of motion control unit (MCU)  604  (to be described in detail further below). 
     Camera  207  of the present disclosure is configured to obtain an image of grains falling from the slot feeder  204 , in curtainlike formation, in front of the first and second background surfaces  205  and  206 . In some exemplary embodiments, camera  207  can be a video camera, a line scan camera, a stills camera, a monochromatic camera, a color camera, an area camera, and any combination thereof, or the like. An area camera is beneficial to be used in the current apparatus since it can capture a significant number of grains on more than one background. The sensor used in the area camera has a large matrix of image pixels so that a usual two-dimensional image can be generated in one exposure cycle, and therefore, its efficiency is enhanced relative to the other options. At least one of the plurality of cameras should be an area camera. Additionally, or alternatively, camera  207  can comprise different wavelengths optical filters (not shown) that may be configured as lowpass, high-pass, bandpass, and any combination thereof, or the like. The filters may be used for color correction; color conversion; color subtraction; contrast enhancement; polarizing; neutral density; cross screen; diffusion and contrast reduction, and any combination thereof, or the like. It should be noted that, the optical filters may be utilized for enhancing spatial, contrast and color resolution of grains (shall be described in detail further below). In some exemplary embodiments, camera  207  can be comprised of a plurality of cameras, wherein each camera of the plurality of cameras can be configured for acquiring different image properties. It should be noted that, the image may be video, at least one still photo, and a combination thereof and wherein the image may be retained in a digital representation. 
     In some exemplary embodiments, the at least one background illumination  214  can be situated in front of the backgrounds, behind the backgrounds, or both, i.e., in front and behind the backgrounds. Additionally, or alternatively, at least one of the background illuminations  214  may have different wave length or can use subtraction filters, intended for color separation. Additionally, or alternatively, one of the surfaces is can act also as an illuminator. 
     In some exemplary embodiments, first background surface  205  can be (however not limited to) white, and second background surface  206  can be (however not limited to) black. It should be noted that, that ROI acquired by camera  207  is configured to capture grains falling in front of the white and black background, i.e. first and second background surfaces  205  and  206 , respectively. In some exemplary embodiments, the first and second background surfaces  205  and  206  may each comprise a grid configured to facilitate image analysis. It will be understood that the white background facilitates analysis of grains pigmentation and or other color defects, whereas the black background facilitate analysis of geometric (shape) defects of grains. In some exemplary embodiments, the second background surface  206  (black) can be recessed with respect to the first background surface  205  (white). The black background is recessed with respect to the white background in order to avoid reflection of the black background onto transparent grains while they are still in front of the white background. In other words, if the black background was flush with the white background the black background could cause artifacts on the grains that face the white background. It should be noted that, an image of the white background is analyzed for color and hue contamination, thus black reflection (artifact) may be confused for contamination. 
     It should be noted that parameters of the background or backgrounds can be manually or automatically changed such as width of each background, positioning of the background one on respect to the other, colors of the backgrounds, etc. 
     Referring now to  FIG. 4  showing a top view of the automated grains inspection apparatus (AIA)  100 , in accordance with some exemplary embodiments of the disclosed subject matter. Slot feeder  204  further comprises a plurality of blades  208 , which are also shown in  FIGS. 2 and 3 . In some exemplary embodiments, the plurality of blades  208  that are organized perpendicularly along the slot feeder  204  can assist in dispensing the grains uniformly across the FOV, i.e., curtainlike formation. The blades  208  also facilitate in regulating the flow of grains through the feeder since the buildup of the grain pile can be controlled. 
     The blades can be moved one in respect to the others, manually or automatically. 
     Referring now to  FIG. 5  is a screenshot of a video frame showing grains in inspection process, in accordance with some exemplary embodiments of the disclosed subject matter. The video frame  500  shows an image of captured grains  501  in the ROI in front of the white section  505  and black section  506 . It should be noted that, the white section  505  enables analyzing grains  501  pigmentation, color and hue qualifications with respect to predetermined thresholds. On the other hand, the black section  506  enables analyzing grains  501  for geometric size, shape, and structural properties qualifications with respect to predetermined thresholds. In cases the grains are dark, the information retrieved from each of the backgrounds is the opposite from the information retrieves for light color grains that are shown in  FIG. 5 . 
     Referring now to  FIG. 6  showing a block diagram of a grains inspection system  600 , in accordance with some exemplary embodiments of the disclosed subject matter. System  600  is a computerized apparatus adapted to perform methods such as depicted in  FIG. 7 . 
     In some exemplary embodiments, system  600  comprises an AIA  100  that is communicating with a processor  601 . Processor  601  is a preferably a central processing unit (CPU), a microprocessor, an electronic circuit, an integrated circuit (IC) or the like. Additionally, or alternatively, system  600  can be implemented as firmware written for or ported to a specific processor such as digital signal processor (DSP) or microcontrollers, or can be implemented as hardware or configurable hardware such as field programmable gate array (FPGA) or application specific integrated circuit (ASIC). Processor  601  can be utilized to perform computations required by system  600  or any of its subcomponents. 
     In some exemplary embodiments of the disclosed subject matter, system  600  can comprise an Input/Output (I/O) Module  602 . System  600  can utilize I/O Module  602  as an interface to transmit and/or receive information and instructions between system  600  and external I/O devices using devices such as mouse, keyboard, or touch screen. In some exemplary embodiments, the processor  601  is comprised within a workstation  605  that comprises also a memory  603 , a display adaptor  608 , a communication module  609 , or the like. The communication module  609  can be interfacing with a network  606 . 
     In some exemplary embodiments, I/O module  602  may be used to provide an interface to a user of the system, such as by providing output, visualized results (such as depicted in FIGS.  5 ,  8 ,  9 , and  10 ), reports, such as grain size, improper cutting monitoring and color/hue defects, or the like on the display  608  using UI or GUI. The user can use workstation  605  to input the information, such as pass/fail thresholds, discarding grains batch, conducting statistic calculations based on previously inspections that are retained in the system or in a network repository. However, it will be appreciated that system  600  can operate without human operation. 
     In some exemplary embodiments, network  606  can be used to facilitate communication between processor  601  with cloud computing server (not shown) such as amazon web services (AWS) having increased and scalability. Additionally, or alternatively, network  606  connection can be used to communicate with another apparatus or a data repository of the production facility. Additionally, or alternatively, system  600  may use network  606  connection for retaining recoded information of the AIA  100  in cloud repository (not shown) or any other network storage. 
     In some exemplary embodiments, system  600  comprises a controller  604 . The controller  604 , interfaced with processor  601  via communication  609  is configured to drive and sense activities associated with electro-mechanic and or pneumatic components of the AIA  100  and the camera  607  within the AIA, such as illumination, image capturing, IOs, and the span of the slot. The controller  604  communicates with the processor  601  and can automatically control the AIA  100 . In some exemplary embodiments, the drive and sense activities can comprise manipulating the inlet funnel  201 ; feeder mechanism  202 ; the slot feeder  204 ; the video camera  207 ; the sorting mechanism  213 ; the background illuminations  214 ; the sliding mechanism  215 ; and any combination thereof, or the like. 
     In some exemplary embodiments, the camera  607  in the AIA  100  is interfacing with processor  601  to transfer the captured images and convey the images in digital representation to the processor  601  for image analysis. In some exemplary embodiments, the images captured from the at least one camera can comprise cameras selected from a group consisting of video cameras, stills cameras, area camera, line scan camera, video cameras, a monochromatic camera, a color camera, and any combination thereof, or the like. 
     In some exemplary embodiments, camera  607  can comprise an array of optical filters (not shown) adapted to be engaged in front of a lens of the at least one camera by the controller  604 . 
     In some exemplary embodiments, system  600  comprises a memory unit  603 . Memory unit  603  can be persistent or volatile. For example, memory unit  603  can be a flash disk, a random access memory (RAM), a memory chip, an optical storage device such as a CD, a DVD, or a laser disk; a magnetic storage device such as a tape, a hard disk, storage area network (SAN), a network attached storage (NAS), or others; a semiconductor storage device such as flash device, memory stick, or the like. In some exemplary embodiments, memory unit  603  can retain program code to activate processor  601  to perform acts associated with any of the steps shown in  FIG. 7 . Memory unit  603  can also be used to retain images captured by camera  607 , a plurality of grain profiles, outcomes of system  600  (reports), image analysis of each inspection sequence, reference profiles comprising thresholds for different types of grains, statistical analysis associated with reference profiles; and any combination thereof, or the like. 
     The components detailed in system  600  can be implemented as one or more sets of interrelated computer instructions, executed, for example, by processor  601  or by another processor. The components can be arranged as one or more executable files, dynamic libraries, static libraries, methods, functions, services, or the like, programmed in any programming language and under any computing environment. 
     Referring now to  FIG. 7  showing a flowchart diagram of a method for grains inspection, in accordance with some exemplary embodiments of the disclosed subject matter. 
     The inspection system  600  actions are based on the data generated by the image processing it preforms by itself regarding the appearance of the pellets. Optionally, additional data is collected by the system  600  from sensors connected directly to the system  600  and/or by data imported from other line control devices on the production line. For example, the system  600  can receive speed, temperature, and/or pressure readings from the production line and use the information from those sensors alone with the information from camera  207  or other cameras in order to deduce the action needed. 
     The data gathered by the system  600  is processed by means of statistical process control tools (SPC), artificial intelligent (AI) algorithms, data trends analysis, and specially written algorithms, in order to predict upcoming failure or point on an existing production failure. 
     In step  701 , a grain profile is obtained. In some exemplary embodiments, a grain profile associated with type of grain to be inspected can be obtained from a data repository of system  600 , such as for example, memory  603  or a storage connected to network  606 . The grain profile can be one of a plurality of grain profiles retained in the repository, wherein each grain profile is associated to different type of grain. In some exemplary embodiments, the types of grains can differ from one another in terms of size, color, shape, transparency, weight, and any combination thereof, or the like. Therefore, each type of known grain may have a profile characterizing it for the AIA  100  of the present disclosure. 
     In some exemplary embodiments, each grain profile of the plurality of grain profile can comprise predetermined parameters associated to the AIA  100  setup. The parameters can comprise: camera configuration, illumination and background setup, span of the slot feeder, and standard thresholds. 
     In step  702 , the slot feeder is set. In some exemplary embodiments, system  600  adjusts the span  211  of the slot feeder  204  to meet the requirements of a grain size as per the parameters of the current grain profile. 
     In step  703 , the background lighting is set. In some exemplary embodiments, system  600  can set at least one of the background illuminations  214  to meet the requirements of the grains color, hue, size and transparency as per the parameters of the current grain profile. It should be reminded that illuminations  214  can be set for illuminating either sides of the backgrounds as well as both sides simultaneously. Additionally, or alternatively, system  600  can cause the illuminations  214  to alternate side illumination during the inspection process as well as dimming the illumination during the process, all in order to improve image resolution of the grains inspection. 
     In step  704 , the camera is configured. In some exemplary embodiments, system  600  can set at least one camera  207  to meet the requirements for detecting impurities, change in geometry, and color of the grains as per the parameters of the current grain profile. Detection requirements can be for example impurities, dark specks or dark gels, dark and bright contaminations, foreign material, discoloration, cross-contamination, color measurement and color shift, size deviation, shape irregularities, agglomeration, transparency, gloss. It should be reminded that, more than one camera can be used simultaneously as previously described. Additionally, or alternatively, system  600  can cause one or more cameras  207  to alternate image capturing during the sorting process as well as engaging optical filters in the image capturing process, all in accordance to the current grain profile. 
     In step  705 , grains pouring is enabled. In some exemplary embodiments, grains can be enabled to enter the inlet funnel to initiate the grain monitoring and inspecting process. 
     In step  706 , an image is captured and analyzed, as well as data that is collected from other sources such as other sensors and/or other line production systems. In some exemplary embodiments, a digital representation of the image can be routed by the video front end  207  to processor  601  for image analysis. The image analysis is configured to determine criteria of each grain in the image, wherein the criteria are selected from a group consisting of requirements for detecting impurities, change in geometry, color of the grains, for example impurities, dark specks or dark gels, dark and bright contaminations, foreign material, discoloration, cross-contamination, color measurement and color shift, size deviation, shape irregularities, agglomeration, transparency, gloss. In some exemplary embodiments, the images are retained in the repository in records of 60 seconds each. 
     In step  707 , histograms are generated from all or part of the data that is collected in step  706 . In some exemplary embodiments, system  600  is adapted to generate a histograms representation, such as depicted in  FIGS. 8 to 16 , for different criterions as listed above, for example. It should be noted that the horizontal axis of each histogram represents dimension, preferably but not necessarily given in microns and the vertical represents incidences, scaled in 100K grains. Each bar of each histogram comprises a representing thumbnail-image per 100K grains. Optionally, additional data, for example data that is collected by means of statistical process control tools (SPC), artificial intelligent (AI) algorithms, data trends analysis, and specially written algorithms, can be used. All the data processed by system  600 , including the SPC and AI can be based also on information from other sensors from other production lines or other sensors from the system. 
     The visual information, for example the histograms, as will be depicted herein after can be connected and displayed for any one of the sorting systems described herein before as well as in other sorting and inspecting systems. 
     The inspecting systems can be used for additional actions—step  708 —such as:
         1. Ejecting of the disqualified pellet using air nozzles or mechanical flaps, this action allows removing the disqualified pellets alone with zero to relatively small number of pellets that were disposed close to it.   2. Diverting of the inspected material stream using a diverter valve, or other mechanism that shifts the entire material flow. This action removes the disqualified pellets with a relatively large number of pellets that are in the material stream with disqualified pellets at the same time.   3. Send a command to the production line control to stop the production, or to set a new set point to one of the production parameters such as speed, temperature, pressure, and/or other parameters in order to prevent the manufacturing of disqualified pellets or to improve their quality.   4. Generate alarms to the productions line operator to give indication on production failure or to indicate that the production is shifting good and stable production to less good or unstable production that may cause production failure if this will not be corrected by the operator.   5. Generate recommendation to the line operator on actions to be taken in order to maintain or achieve good and stable production.       

     In some exemplary embodiments, the sorting or other actions are executed based on predetermined parameters of a given grain profile that comprise standard thresholds. The thresholds dictate predetermine pass/fail discrimination levels for each criterion. System  600  can also generate quality reports. 
     Reference is now made to  FIGS. 8, 9, and 10 .  FIG. 8  shows a histogram of blackness criteria measured in grey levels;  FIG. 9  shows a histogram of black size criteria measured in microns; and  FIG. 10  shows a histogram of grain size criteria measured in microns. In some exemplary embodiments of the disclosed subject matter, system  600  can react to any deviation from the standard in one or more than one actions described in step  708 . It should be noted that other parameters can be monitored, inspected, and represented in the histograms such as grain size, grain shape, contamination size and shape, color deviation, absolute color of the grains or items, etc. 
     Referring now to  FIG. 11  showing a workstation screenshot depicting an outcome report, in accordance with some exemplary embodiments of the disclosed subject matter. Accuracy and reliability of inspecting systems depend very much on the competence and working quality of the system operators, the correct management of the setting up and controlling the inspecting system. In reality, this sets out several very serious challenges to users, even to the experts. Once a user is operating the inspecting system, at least two types of information representations are important in order to give the system the correct instructions and to effectively conduct the inspecting process: statistical information and images information. In accordance with embodiments of the disclosed subject matter, the user is capable of interfacing and providing the instructions to the inspecting apparatus based on a statistical analysis combined with the captured images so that both types of information are simultaneously presented to the user. This feature will be further elaborated hereinafter. The upper part of screen  220  displays a control indicator  811  showing the status of the results of the current inspection task. According to an embodiment of the current subject matter, control indicator  811  comprises indications on number of ejections and on size. In the event that the status is normal, the control indicator  811  is green. In the event that the status is not normal, the control indicator  811  will be marked as yellow or as red. Any other colors are possible to be used without limiting the scope of the present subject matter. Optionally, more than one control indicator  811  can be shown on screen  220 , showing indication of several factors according to the operator&#39;s request, for example, showing inspection tasks that failed or predictions for failure. The central part  810  of screen  220  displays visual information about the inspected objects. According to this embodiment, this screenshot shows a display of the inspected objects during a process of pellets with dark contamination inspection. In mode tab  812 , several display modes are presented, and the user can change from one mode to the other. In this embodiment, the display mode is in a form of thumbnail pictures. In thumbnail mode live or reference views of a specific task at a specific time is presented. Another display mode is trend, showing a graphic view of the monitored parameters for a chosen time interval as will be further described in  FIG. 12 . Another display mode is camera view. State tab  814  has at least two states-live view and reference view, as will be further described in  FIG. 13 . The central part  810  of screen  220  shows thumbnail of the pellets which are relevant for the task. Line  816  is operated to set discrimination level. Each square  818  is a representation of an object that is inspected in AIA  100 . Screen  220  can display a plurality of squares  818  representing the inspected population. The latest images are displayed on central part  810  appear on the bottom of screen  220 , pushing the images of prior squares  818  up, in a first-in-first-out stack manner. The number of squares  818  that are displayed, are associated with the number of specific grains and the height of the central part  810 . On the right-hand side of the central part  810 , only one type of the specific grain is detected and therefore, only this specific one is displayed in a thumbnail, however, on the left-hand side of the central part, more than 4 thumbnails are present but only four of them are shown. If the height of the central part would have been higher, more thumbnail pictures would have been presented. The lower part  820  of screen  220  displays a quantified date in a histogram view. Optionally, squares  818  can display images according to a criteria determined by the operator, for example best image quality items or most suitable representing image. 
     General task boxes comprise tech login box  822 , golden reference box  824 , histogram box  826 , flow box  828 , HW box  830  and fleeting box  832 . Tech login box  822  comprises login button  8221  and logout button  8222  to be pressed by the user entering and exiting the system. Golden reference box  824  is used to set a snapshot of a golden reference during an inspection, either the current inspection task or generally for more than one inspection tasks. Once save button  8241  is pressed by the user, the current thresholds as well as all other decisions and parameter settings that apply will be saved as a golden reference. Once the load button  8242  is pressed by the user, a graphic interface of the golden reference is shown on screen  220 . Histogram box  826  shows the current task. The user can scroll down the list of options of tasks that appear in the histogram box, for example defect contrast, defect size, pellet size, unfocussed, yellowness and the like. When clear histograms button  8261  is pressed by the user, the histograms shown in central part  810  of screen  220  are cleared and the central part  810  of screen  220  is empty. Flow box  828  shows on the left-hand side the count of pellets per minute  8281 . Flow box  828  shows on the right-hand side the percentage of separation of the pellets  8282  is shown. Cloggings bar  8283  shows a visual indication of the flow of the inspected grains in funnel  201 . If the flow is good, cloggings bar  8283  will be green. If there are obstacles or if the flow is not good, cloggings bar  8283  will red. HW box  830  ejection disabled button  8302  can be either red or green, and the color changes upon pressing the ejection disabled button  8302 . Once report button  8304  is pressed, a report of the current task is being generated and sent to the user. At the bottom of HW box  830 , an indication part  8305  shows whether ejection is disabled. Fleeting box  832  is used when an ejection enablement is done using ejection disabled button  8302 . In fleeting box  832  the user can indicate by checking the box in the name button  8321 . Preferably, the name is the description of the task, and a counter of the number of ejections that occurred is shown. The user can reset the count of the fleets by checking the counter button  8322 . 
     According to one embodiment of the disclosed subject matter, both types of information discussed herein before, are displayed on screen  220 , allowing the user a broad view of the results of the inspection process. On central part  810 , thumbnails view of the images of the inspected items appears. On corresponding lower part  820 , histogram view of the statistical information about the inspected items appears. Specific square  818 , which is part of column A###, is a thumbnail image of an inspected item that is part of a group that appears in that column. For example, column A ### is a segment of inspected items in a task named defect size as appears in histogram box  826 . As described before, if the height of the central part  810  would have been higher, more thumbnail pictures could have been presented—all from the same group. Statistical information related to the items that are displayed in column A###, for example the intensity distribution of the parameter, is shown in the corresponding histogram bar B###. In some embodiments of the current subject matter, at the button of each column A###, a synopsis of the statistical information is displayed. Having the ability to simultaneously explore the corresponding two types of information, statistical and visual, gives the user better understanding of the inspecting task and of the specific items being inspected. Based on the image information, the user can decide whether the irregularity is severe and decide if an instruction to the system needs to be given. Based on the statistical information, the user can make decisions related both to the specific corresponding image or images as well as to the entire inspecting task. For example, the highest peak of the histogram represents the location of the value that occurs most often in a data set, also called the mode of the data set. This statistical information is changing during the inspection process, and can affect instructions and decisions made by the user. Having a simultaneous view of the image information in column A## in reference with the peak or mode in the correspondence histogram gives the user a wide and relevant knowledge base for analysis and instruction generating. For example, threshold setting can be done more efficiently since the operator can examine the images in light of the statistical information. In some cases, for example, the operator can realize that a defect size threshold that was set is too rigorous, and the size of the defect can be larger before an item is categorized as defected. 
     Referring now to  FIG. 12  showing a workstation screenshot depicting an outcome report in trend view, in accordance with some exemplary embodiments of the disclosed subject matter. In trend view, the information is displayed as a graph of the monitored parameters for a chosen time interval, for example several hours or days. Duration box  902  comprises at least one button showing the time interval for viewing. By pressing one of the buttons in duration box  902 , the relevant information is displayed. For example, when pressing the 24 hours button, as shown in  FIG. 12 , the information from the last 24 hours is displayed. Parameters checkbox  904  lists the parameters that can be monitored, for example black detections, ejections, ejections last 10 minutes, grain per minute average, small over threshold, grain size and the like. In central part  810  of screen  220  a graphic view of the parameters&#39; information and the change during the time. On the right-hand side of central part  810  of screen  220 , the graphic legend  906  appears, showing the specific graphic representation of each parameter. For example, black detections are marked in green, ejections are marked in light brown, ejections last 10 minutes are marked in dark red, grain per minute average are marked in blue. By clicking a specific dot  908  the interface changes to be of the thumbnail view as described before. It should be noted that any combination of colors is possible. Trend view allows the user to visually evaluate historical information about prior tasks at a certain time, and to set thresholds according to such information, as will later be explained in  FIGS. 14A, 14B, 15A and 15B . 
     Referring now to  FIG. 13  showing a workstation screenshot depicting an outcome report in thumbnail view, in accordance with another embodiment of the disclosed subject matter. In thumbnail mode, view button  910  has two modes that the user needs to check—live view or reference view. If live view is pressed, the display is of view of the current inspection run. In the event that reference view is pressed, the display is of another run such as the golden reference or any other historical reference. In reference box  912 , description of reference is displayed, and the user presses the option he wants to be displayed—golden, single, range or none. In the lower part  820  of screen  220 , view of two histograms is displayed—blue for live view and green for reference view. Other colors can be chosen. Display of histograms of both current inspection task and general task statistical information allows the user to explore and compare the information in order to make an informed decision. General task statistical information can be, for example, information about similar tasks in a chosen time interval or a golden reference graphic information. For example, having wealth of information about current task in relation with other tasks in the specific system as well as in other apparatuses so as to compare the results in the different systems can give the operator an indication about the production line. Another example is comparing inspection of items from one production batch to another. Such information can be monitored over time to get insights on how to improve the production. 
     Referring now to  FIG. 14A  showing a workstation screenshot depicting an outcome report of dark defects inspection in thumbnail view, in accordance with some exemplary embodiments of the disclosed subject matter. Setting threshold value or discrimination level is a common activity done by a user of an inspecting system in order to define objectives related to specific inspection or analysis task. User can use threshold values to define a key performance indicator (KPI) value from which the item is good or critical. Green line  920  and green line  922  are set by the user. The green lines  920  and  922  are setting a discrimination level for the allowed number of small contaminations in the range of 200-400 micron. Optionally, an alarm is activated if the number accedes 1000, as is shown in line  140   FIG. 14B . Red line  924  is setting a discrimination level for sorting dark contaminations above 700 microns. In the lower part  820  of screen  220  the corresponding histogram view is displayed. For example, in column  926  a thumbnail display of 3.9 pellets with dark defects in the size of 800 microns (normalized to 100 k pellets) is displayed. The corresponding histograms display is shown in bar  928 . 
     Referring now to  FIG. 15A  showing a workstation screenshot depicting an outcome report of size monitoring inspection in thumbnail view, in accordance with some exemplary embodiments of the disclosed subject matter. Discrimination ranges or threshold ranges result from the threshold values, e.g., target range and critical range. Depending on the threshold range in which a KPI value is, it is good or critical, for example. Green line  920  and green line  922  are set by the user. The green lines  920  and  922  are setting a discrimination level for the allowed number of small particles (normalized to 100 k pellets) in the range of 300-1200 microns. An alarm is activated if the number accedes 3 k, as is shown in line  150  of  FIG. 15B . Red line  924  and red line  926  are setting a discrimination level for the allowed change in the mode of the histogram. An alarm is activated if the mode change is lower than 2.3 mm or if the mode change accedes 2.6 mm. 
     Referring now to  FIG. 16  showing a workstation screenshot depicting an outcome report of yellowness inspection in thumbnail view, in accordance with some exemplary embodiments of the disclosed subject matter. Green line  920  is setting a discrimination level for too yellow pellets. 
     Other parameters can be displayed in the same or similar manner. 
     Although the invention has been described in conjunction with specific embodiments thereof, it is evident that many alternatives, modifications and variations will be apparent to those skilled in the art. Accordingly, it is intended to embrace all such alternatives, modifications and variations that fall within the spirit and broad scope of the appended claims. All publications, patents and patent applications mentioned in this specification are herein incorporated in their entirety by reference into the specification, to the same extent as if each individual publication, patent or patent application was specifically and individually indicated to be incorporated herein by reference. In addition, citation or identification of any reference in this application shall not be construed as an admission that such reference is available as prior art to the present invention.