EP2467808A1 - Dispositif et procédé d'identification d'objets utilisant un codage morphologique - Google Patents

Dispositif et procédé d'identification d'objets utilisant un codage morphologique

Info

Publication number
EP2467808A1
EP2467808A1 EP10809632A EP10809632A EP2467808A1 EP 2467808 A1 EP2467808 A1 EP 2467808A1 EP 10809632 A EP10809632 A EP 10809632A EP 10809632 A EP10809632 A EP 10809632A EP 2467808 A1 EP2467808 A1 EP 2467808A1
Authority
EP
European Patent Office
Prior art keywords
value
elements
image
repeating
processor
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP10809632A
Other languages
German (de)
English (en)
Inventor
Ran Kaftory
Ronen Horovitz
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Eyecue Vision Technologies Ltd
Original Assignee
Eyecue Vision Technologies Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Eyecue Vision Technologies Ltd filed Critical Eyecue Vision Technologies Ltd
Publication of EP2467808A1 publication Critical patent/EP2467808A1/fr
Withdrawn legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B1/00—Manually or mechanically operated educational appliances using elements forming, or bearing, symbols, signs, pictures, or the like which are arranged or adapted to be arranged in one or more particular ways
    • G09B1/32—Manually or mechanically operated educational appliances using elements forming, or bearing, symbols, signs, pictures, or the like which are arranged or adapted to be arranged in one or more particular ways comprising elements to be used without a special support
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/22—Image preprocessing by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition
    • G06V10/225—Image preprocessing by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition based on a marking or identifier characterising the area
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/46—Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B5/00—Electrically-operated educational appliances
    • G09B5/02—Electrically-operated educational appliances with visual presentation of the material to be studied, e.g. using film strip

Definitions

  • This application relates to computer vision, and particularly to identifying an object in an image captured in uncontrolled lighting conditions, where the identification is based on repeating units of morphological code that appear on the object.
  • Identification of objects in an image captured by a digital imaging device may rely on extracting features of the object and use pattern recognition of those features to identify the object.
  • Pattern recognition and feature extraction may be subject to inaccuracies caused by, among other things, lighting conditions, changes in object orientation, relative distance of the object from the imager and occlusion.
  • Typical identification processes may therefore entail rotation, translation and scale invariant features, and may call for complicated pattern recognition algorithms. Adding an object to the recognition task may therefore require adjusting a recognition algorithm compensation for lighting condition.
  • An embodiment of the invention may include a method of identifying an object by capturing an image of the object, where in the image is detected a repeating reference form and a set of elements that are at a pre-defined distance from and orientation to the repeating reference form.
  • a value may be derived from the set of elements, and that value may be compared to a stored value that is associated with the object.
  • the derived and detected value of the elements in the image may confirm the object in the image as matching the object having the associated value stored in the memory.
  • Instance of the repeating units may appear on a perimeter of an object or elsewhere, and the repetition of the units may compensate for occlusion of some of the units or a failure of the imager to clearly capture one or more of the units or elements.
  • a derived value of an element may be determined on the basis of its length relative to the alignment bar, such as a length along a perimeter of the alignment bar, or by a perpendicular height of an element to the alignment bar, such as a distance of an end of the element from its base as is connected to the alignment bar.
  • an element representing a "0" may be an absence of an element along a spot on an inner edge of an alignment bar.
  • a "1" may represent the presence of an element along a position on an inner edge of an alignment bar. Values may also be derived from other heights, thicknesses, shapes or sizes of elements relative to each other or to the alignment bar.
  • the elements may be connected to and may follow a curve of the alignment bar or reference form, and may be of a same or designated color or groups of colors relative to the reference form
  • a value may be derived from more than one set of elements detected in the image, and the values may be compared for purposes of confirming the accuracy of the detected image and computation of the value.
  • a value may be derived from a third set of elements and compared to the other two values. If derivations for two out of three, or some other proportion, of elements yield the same value, such value may be assumed to be the value appearing in the image. Further derivations of sets of elements may be undertaken to add robustness to the identification.
  • a unit may be detected on the basis of it including a reference form such as an alignment bar and elements connected to, or at a known orientation to, the reference form.
  • a reference form such as an alignment bar and elements connected to, or at a known orientation to, the reference form.
  • a processor may issue a signal upon the confirmation of identification of an object in the image.
  • an imager may capture and detect a unit and a set of elements at a distance of up to 5 meters.
  • Some embodiments of the invention may include a system of an object having appearing thereon repeating reference forms and a set of elements at a pre-defined orientation and distance from the repeating reference form, and a processor to calculate a value associated with the elements and to compare the value to a value stored in a memory.
  • Some embodiments may include a medium to store a set of instructions that may be executed by a processor, where, upon such execution, the processor translates a numeric value into a set of non-numeric binary shapes and creates an insert item to a print file that includes the shapes oriented to a known position relative to a reference form.
  • the item may be added to a print file in repeating units around for example a perimeter of an image of the object that is to be printed.
  • the repeating unit may appear in the printed image at a known position relative to the image of the printed object.
  • the repeating units may be configured or added to the print file to conform to a shape of the printed object.
  • the repeating units may form a round frame around the printed face.
  • the repeating units may be added to the print file so that they appear at least at a minimum distance from the object being printed, such that the elements do not overlap or touch the printed image.
  • the instructions may associate the printed object with the value that was translated into the elements.
  • a processor may generate a set of shapes on an alignment bar that have a value of 23, and add repeating units of the shape around a printed round face.
  • the printed round face may be associated in a memory with the value 23 so that, upon a later detection of shapes that yield a value of 23, the processor may signal a detection of the round face.
  • Fig. 1 is a schematic diagram of a system including an imaging device, a processor, and an object to be identified in accordance with an embodiment of the invention
  • Figs. 2 A and 2B are examples of objects that may be identified in accordance with an embodiment of the invention.
  • Fig. 3 is a flow diagram of a method in accordance with an embodiment of the invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
  • the term 'morphological' may, in addition to its regular meaning, imply that a first shape emerges from a second shape.
  • a shape in an image that may indicate a bit of information may be attached to, continue, emerge or morph from an alignment bar, such that the detection of the shape representing the bit may be associated with or related to the detection of the shape or presence of the alignment bar.
  • Fig. 1 is a schematic diagram of a system including an imaging device, a processor, and an object to be identified in accordance with an embodiment of the invention.
  • a system 100 may include for example a screen or display 101 that may be connected to or associated with a processor 106, and an imager 102 that may capture an image of an object 104, and relay or transmit digital information about the image to processor 106.
  • Object 104 may include or have printed or placed thereon various shapes 108 that may be arranged for example in a known or pre-defined pattern, on an area of object 104, such as a rim or perimeter 110 of object 104 or on other known areas of object 104, such that such shapes 108 are visible to imager 102.
  • such shapes may be or include monochromatic morphological shapes.
  • on a middle or other part of object 104 there may be affixed, attached or printed a mark, such as a shape, number, letter, drawing or other figure 112 to be identified.
  • a list of patterns of shapes 108 may be associated with one or more objects 104 or figures 112 that may be attached to object 104, and such lists and associations may be stored in a memory 114 that may be connected to processor 106.
  • display 101 may show or display figure 112, such as a letter A, to for example, a user.
  • User may then find an object that matches or otherwise corresponds to the displayed figure 112, such as a card or other object that may have a letter A printed on or attached to it.
  • User may raise or otherwise expose the object 104 to imager 102, which may capture an image of the object 104 and of the shapes 108 that may be printed on, attached to or otherwise make up a part of object 104.
  • the image may be transmitted to processor 106 which may find or discern the pattern of the monochromatic morphological shapes 108 on the object 104 in the image.
  • Processor 106 may search memory 114 for a numerical or other value of the identified pattern of shapes 108, and may determine that the particular pattern of shapes 108 that appeared on the object 104 in the image is associated with a value that may have been assigned to figure 112 that was shown on display 101. Upon a detected match between the displayed figure 112 and the object 104 that was exposed to the imager, processor 106 may issue a signal to for example to an audio, visual or other indicator or calculator, such as a bell or speaker 116, to indicate that the figure on object 104 that was captured in the image corresponds to the figure shown on display 101. For example, a letter A may be associated with a value 23 as such value and association may be stored in memory 114.
  • a card having a letter A as a figure 112 may include a shape 108 pattern that is also is associated in memory 114 with a value 23.
  • Processor 106 that signaled display 101 to show an A to a user, may detect a match between the value associated with the displayed figure 112 and the value indicated by the pattern of shape 108.
  • a pattern of shape 108 may be identified even if the image is captured in an uncontrolled environment, such as for example against a nonuniform background such as a colored wall or curtain, and under uncontrolled lighting and shadow conditions, such as direct or indirect light, sunlight, indoor ambient light or other non-uniform lighting conditions.
  • an uncontrolled environment such as for example against a nonuniform background such as a colored wall or curtain
  • lighting and shadow conditions such as direct or indirect light, sunlight, indoor ambient light or other non-uniform lighting conditions.
  • a pattern of shapes 108 may be identified even if an orientation of object 104 relative to imager 102 is other than perpendicular to the light entering or reflecting back to imager 102.
  • object 104 may be held at an acute or other angle to imager 102, may be rotated, partially occluded by for example interfering objects such as a hand of a user, or otherwise incompletely imaged, and imager 102 may still be able to detect and identify at least one or a part of the repetitive pattern of shapes 108.
  • a pattern of shapes 108 may be identified at various distances of object 104 from imager 102, such as for example from 10 cm to up to 5 meters or more.
  • the distance from imager 102 at which a pattern of shapes 108 of object 104 may be identified may be dependent on for example a resolution of imager 102 and may allow the determination of the distance of the object 104 from the imager 102.
  • processor 106 may determine a size of a first shape 108 and a size of a second shape 108 in the image on the basis of the number of pixels in the captured image that include the first shape 108 and the second shape.
  • imager 102 may be or include a suitable digital imager such as a CCD, CMOS or other video or still digital image capture device capable of capturing and transmitting color or intensity image data.
  • a low resolution camera such as those typically included in a web-cam or network capable camera configuration, having a resolution of QVGA or VGA may be suitable for an embodiment of the invention.
  • processor 106 may be or include an embedded processor or a DSP or a Pentium ® IV or higher processor or other comparable processor typically used in a home computing configuration.
  • Memory 114 may be or may be included in any suitable data storage device such as a hard drive, flash, or other electronic data storage on which may be stored for example a data base, array, tree or other data storage structure.
  • display 101 and bell or speaker 116 may be or be included in a single device such as for example a display and sound system that may indicate to a user that a match or other action is correct, incorrect or otherwise responsive to a question, challenge or other signal posed to the user.
  • processor 106 may be an embedded processor which is housed inside an object such as a mobile phone, toy, doll or toy housing.
  • imager 102 and bell/speaker 116 may be or be included inside the doll or toy or toy housing.
  • Figs. 2 A and 2B are examples of objects that may be identified in accordance with an embodiment of the invention, and expanded views of the repeating codes and alignment bars on a perimeter of such objects.
  • objects 200 and 2B are examples of objects that may be identified in accordance with an embodiment of the invention, and expanded views of the repeating codes and alignment bars on a perimeter of such objects.
  • objects 200 and 2B are examples of objects that may be identified in accordance with an embodiment of the invention, and expanded views of the repeating codes and alignment bars on a perimeter of such objects.
  • objects 200 and 201 may be or include a flat, spherical, cubical or other shaped object that may be suitable to be moved, raised or otherwise maneuvered by for example a user or some other system to be brought into an area to be imaged by imager 102.
  • objects 200 and 201 may be a card or disc that may be or include cardboard, plastic or other semi-rigid material.
  • Objects 200 and 201 may include a ball, toy, manufactured device or other item as long as the monochromatic morphological shape pattern can be printed, attached, stamped on or stuck to it.
  • Attached or imprinted on for example an outside perimeter of object 200 may be a series of shape code 202 that may create a pattern of for example repeating or repetitive monochromatic binary codes.
  • Monochromatic morphological shape codes may be used to create a pattern of for example repeating or repetitive monochromatic binary codes.
  • alignment bar 204 may consist of a reference form such as an alignment bar 204 or alignment curve (shown by horizontal lines for visualization purposes in Fig. 2) and data bits 206 (shown by diagonal lines for visualization purposes in Fig. 2).
  • alignment bar 205 may be curved or may assume some other shape or geometrical form.
  • code 202 may be binary and may be read from right to left, or otherwise in accordance to the position of alignment bar 204. A dark bit may be read as "1" while a light bit may be read as "0".
  • Alignment bar 204 and data bits 206 may be colored with any color which may provide contrast to the background color of object 200.
  • the proportions of the code 202 elements are depicted in the expanded views of codes and alignment bars in Figs 2 A and 2B. Other proportions and dimensions are possible. In some embodiments, a maximum distance from which this code is recognized by an imager may depend on the code 202 units being detected by even a single pixel in the image.
  • code 202 may be depicted along a curved plane of bar 205 as the proportions of the sides of bits 206 of code 202 are maintained relative to each other and to bar 5.
  • Shapes 202 may form any geometrical shape (e.g., lines, circles etc.) or may take on other configurations.
  • the pattern of code 202 may be marked on object 200 on one, some or all sides exposed to the imager.
  • Object 200 may include any tactile object to which code 202 may be affixed or on which code 202 may be shown.
  • Sequences of monochromatic morphological shape codes 202 may include at least two binary bits, though the variations of codes and hence the number of items or figures 206 associated with a distinct pattern of monochromatic morphological shape code 202 may increase with increased number of bits 206 included in the monochromatic morphological shapes 202.
  • the size of each monochromatic morphological shape 202 may be determined by, for example, the intended distance between object 200 and imager 102 as well as by the resolution of imager 102.
  • Localization of the monochromatic morphological shapes 202 around a perimeter, rim, edge or other pre-defined area of object 200 may avoid the effects of occlusion of a portion of code 202, and may provide more robust detection and identification of code 202 once the object 200 is detected in an image. Similarly, repetition of the pattern may allow identification of the pattern even when the object is partially occluded or when an orientation of object 200 in an image partially blocks its exposure to the imager 102.
  • a particular monochromatic morphological shape code 202 such as for example binary code 10101, may be pre-defined and stored in memory 114, where the pattern may be associated with a value that may be further associated with an object or figure.
  • a monochromatic code may designate a binary code in a pattern, in which case the number of combinations may be defined as
  • an additional feature may be used to increase the number of possible codes such as the color of the monochromatic code. Polychromatic combinations or codes may be possible, such that if r different colors are used, the formula becomes:
  • even more features may be used to increase the number of possible codes such as the color of the background of the monochromatic code. If r different colors are used and k different background colors are used, then the formula becomes:
  • a two sided binary coding scheme may be used, whereas for the same width and an increase in the height of the code may be used, so long as such increase in height is distinguishable by the imager.
  • Detection and identification of a bar or code in a captured image may entail some or all of the following processes.
  • Identification of captured edges that form closed contours where such identification may be performed using a connected component algorithm such as a regular labeling operation. Such identification may detect the presence of edge contours which comply with the pre-defined ratios of the alignment bar, code or object to one or more of each other.
  • a length of the alignment bar may be used to measure the absolute distance from the imager of the object containing the code, where for example the real world size of the printed code is known a priory.
  • the shape, alignment bars and codes may be repetitive, so it is likely that more than one sequence of the pattern appears in the image.
  • a probability function for the pattern may be used to verify the object classification by taking into account, not only the presence of a code or pattern and the number of times it appears, but also the number of adjacent sequences or other spatial based relation between such repetitions such as distance or dispersion.
  • the pattern with the highest probability may be chosen as representing the pattern associated with the correct code and the associated object.
  • this procedure may be applied in consecutive frames of an image and the confidence of classification may be increased if a same pattern is selected on a few or consecutive frames.
  • shape patterns may be attached to objects such as empty cards with no figure on them, and the user may adhere an image or draw an image on the blank cards.
  • a pattern associated in memory with "My Pet” may be attached to a picture of a user's pet, and the blank card may be recognized by the system as being associated with the pet.
  • patterns of shapes may be camouflaged or even non- discernible to the human eye, as they may be implanted within a picture or item that is observed by the imager in a way which is integrated into the printed figure itself.
  • a letter, number or figure may be drawn to include a shaped pattern that may be identified by the imager but hidden from obvious discernment by a user.
  • shape patterns within a picture or on an item may be printed using an ink that is not reflective in the visible light spectrum such as IR or near IR, and the imager that captures the image may be an IR camera.
  • a micro-code version of shapes and codes may be affixed to an object to create a more camouflaged version of coded objects.
  • detection of a shape that includes a code may include subtraction process to isolate objects in a second image that was not included in a first or prior image on the assumption that the object that includes the shape was introduced into the view of the imager subsequent to the capture of the first image. Such subtraction may reduce the number of attempts or calculations required to detect the object in a series of images.
  • the recognition of the coded objects may be used as part of an educational curriculum for children or students.
  • the recognition of coded objects may be associated with answers to questions, for example, upon an instruction to "Hold up an animal card!, the student holds up an animal card coded with the monochromatic shapes that are associated with cards showing pictures or names of animals.
  • the system may detect the codes and recognize the code number and respond with "That's a bear!” This process may be expanded to a classroom equipped with a computer and one or more imagers where the computer recognizes different objects or cards for a full class experience with multiple students, one or more of whom may hold up a correct or incorrect card or object.
  • recognition of the objects having shapes and codes may be used as part of an interaction with a customer. For example: a customer waiting in a restaurant who wants to get the attention of a waiter may hold up a coded image or other coded object, and a camera in the restaurant may detect the coded image and send the location of the table along with the code number, which can be associated with "Please bring me the check" or other message.
  • detection or identification of a particular code may elicit a computerized or automated response, by for example a mobile phone whose camera may detect a presence of a shape or code and display on the phone's screen an animation sequence related to that object associated with the code, or dial a number related to the object.
  • coded patches, images or even shirts can be used to track the location of people or animals in a farm. Different locations in the surroundings may have cameras connected to a computer which recognizes the people or animals when they cross a field of view of a camera.
  • coded objects or cards can be used to navigate to different websites by showing the coded objects or cards to a webcam associated with a computer, for example, showing a coded car from the movie "TransformersTM” may send the browser in a computer to the relevant TransformersTM website or showing a coded image of a BarbieTM doll may direct the browser to the BarbieTM website.
  • a flow chart of a method in accordance with an embodiment of the invention may include a method of identifying an object, where such method includes, as in block 300, detecting in an image a repeating reference form and a set of elements, where the set of elements is at a pre-defined distance from and orientation to the repeating reference form.
  • a reference form may be a curved or straight alignment bar, and the elements may jut out from the alignment bar at for example a perpendicular angle.
  • a value may be derived from the image of the elements.
  • the derived value may be compared to a value stored in a memory, where the stored value is associated with the object.
  • an image of the object may be captured at a distance from the imager from a distance of up to 5 meters.
  • the detecting may include detecting elements that are connected to the alignment bar, and where deriving a value includes deriving a first value from a first set of elements and a second value from a second set of elements, and comparing the values to determine if they are the same. If the values are not the same, in some embodiments a third value may be selected from a third set of elements and a comparison of the third value to each of the first and second values may be made. A value that is derived from two or more of the sets may be assumed to be the true value.
  • the elements may be recognized as elements only if they are connected or at a defined distance or orientation from the alignment bar or reference form.
  • a signal may be issued indicating such match to the user.
  • the nature or meaning of an element may be derived from a size or length of the element of from a distance of the element from the reference or alignment bar.
  • a single element of the set of elements may represent either a zero or a 1.
  • the elements may have different colors and may be differentiated by such colors.
  • a series of instructions in the form of, for example, software may be stored in an electronic storage medium and executed by a processor to translate a numeric value into a set of non-numeric binary shapes such as those that may extend from an alignment bar.
  • the processor may orient the shapes at a known position relative to the alignment bar, such as connecting at a perpendicular angle to the bar, and add repeating units of alignment bars and the set of shapes to a print file that includes an image around which are to appear the repeating units.
  • the repeating units may appear around or on a side or elsewhere on the printed image.
  • the shape of the printed repeating units may conform to an outline of the printed image and may be printed at a given or minimum distance from an edge of the printed image.
  • the instructions may store the value represented by the elements along with an association of such value with the printed object.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Multimedia (AREA)
  • Business, Economics & Management (AREA)
  • Educational Administration (AREA)
  • Educational Technology (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Image Analysis (AREA)

Abstract

L'invention concerne un procédé et un système permettant de détecter une unité répétée dans une image, ladite unité comprenant une forme de référence et un ensemble d'éléments se situant à une distance et dans une orientation connues par rapport à la forme de référence; calculer une valeur à partir des éléments compris dans l'unité; et comparer la valeur calculée à une valeur connue. Les éléments peuvent indiquer des valeurs binaires pouvant être utilisées dans le calcul de la valeur, et la valeur peut être associée à un objet. Une comparaison entre la valeur calculée à partir des éléments contenus dans l'image et la valeur stockée associée à l'objet peut servir à identifier ou à confirmer l'identification de l'objet dans l'image.
EP10809632A 2009-08-17 2010-08-17 Dispositif et procédé d'identification d'objets utilisant un codage morphologique Withdrawn EP2467808A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US27442709P 2009-08-17 2009-08-17
PCT/IL2010/000668 WO2011021193A1 (fr) 2009-08-17 2010-08-17 Dispositif et procédé d'identification d'objets utilisant un codage morphologique

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EP2467808A1 true EP2467808A1 (fr) 2012-06-27

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EP (1) EP2467808A1 (fr)
JP (1) JP2013502634A (fr)
CN (1) CN102696043A (fr)
WO (1) WO2011021193A1 (fr)

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WO2013065045A1 (fr) * 2011-10-31 2013-05-10 Eyecue Vision Technologies Ltd Système pour des jouets et des jeux basés sur une reconnaissance de vision, actionné par un dispositif mobile
JP5862623B2 (ja) * 2013-08-08 2016-02-16 カシオ計算機株式会社 画像処理装置、画像処理方法及びプログラム
DE102014009686A1 (de) 2014-07-02 2016-01-07 Csb-System Ag Verfahren zur Erfassung schlachttierbezogener Daten an einem Schlachttier

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US8301893B2 (en) * 2003-08-13 2012-10-30 Digimarc Corporation Detecting media areas likely of hosting watermarks
US7204428B2 (en) * 2004-03-31 2007-04-17 Microsoft Corporation Identification of object on interactive display surface by identifying coded pattern
CN101163234A (zh) * 2006-10-13 2008-04-16 杭州波导软件有限公司 利用数据处理装置进行模式识别和图像监控的实现方法

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WO2011021193A1 (fr) 2011-02-24
CN102696043A (zh) 2012-09-26
JP2013502634A (ja) 2013-01-24

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