Search Images Maps Play YouTube News Gmail Drive More »
Sign in
Screen reader users: click this link for accessible mode. Accessible mode has the same essential features but works better with your reader.

Patents

  1. Advanced Patent Search
Publication numberUS20040199531 A1
Publication typeApplication
Application numberUS 10/831,005
Publication dateOct 7, 2004
Filing dateApr 23, 2004
Priority dateDec 1, 1999
Also published asDE60033118D1, DE60033118T2, EP1107136A1, EP1107136B1, US6754667, US20020010704
Publication number10831005, 831005, US 2004/0199531 A1, US 2004/199531 A1, US 20040199531 A1, US 20040199531A1, US 2004199531 A1, US 2004199531A1, US-A1-20040199531, US-A1-2004199531, US2004/0199531A1, US2004/199531A1, US20040199531 A1, US20040199531A1, US2004199531 A1, US2004199531A1
InventorsWhoi-Yul Kim, Yong-Sung Kim, Young-Sum Kim
Original AssigneeKonan Technology Inc.
Export CitationBiBTeX, EndNote, RefMan
External Links: USPTO, USPTO Assignment, Espacenet
Content-based image retrieval system and method for retrieving image using the same
US 20040199531 A1
Abstract
A content-based image retrieval system retrieves an image based on an angular radial transform (ART) image descriptor. In the content-based image retrieval system, A method for retrieving an image includes the steps of: a) receiving a query image; b) extracting a query image descriptor from the query image based on at least an angular component and a radial component of the query image; c) comparing the query image descriptor with an image descriptor stored on the database; and d) determining a degree of a similarity between the query image descriptor and the image descriptor stored on the database.
Images(6)
Previous page
Next page
Claims(8)
1-33. (Cancel)
34. Data stream for use in retrieving an image, the data stream transmitted from a web browser to a web server, comprising:
a retrieval request signal; and
an image descriptor extracted from an image based on an angular component and a radial component of the image,
wherein the image descriptor includes j (j is a natural number) ART coefficients each of which is expressed as:
F n m = < V n m ( ρ , θ ) , f ( ρ , θ ) > = 0 2 π 0 1 V n m * ( ρ , θ ) , f ( ρ , θ ) ρ ρ θ
where, Fnm is an ART coefficient of order n and m, n and m are integer numbers, Vnm(ρ,θ) is an ART basis function, ƒ(ρ,θ) is an image in polar coordinates, and * denotes a conjugate complex number.
35. (Cancelled)
36. The data stream as recited in claim 34, wherein the ART coefficient includes an ART basis function expressed as:
V nm(ρ,θ)=A m(θ)R n(ρ)
where, Am(θ) is an angular function and Rn(ρ) is a radial function.
37. The data stream as recited in claim 36, wherein the angular function Am(θ)includes an exponential function having rotation invariance, which is expressed as:
A m ( θ ) = 1 2 π exp ( j m θ )
where, θ is an angle from an x-axis.
38. The data stream as recited in claim 34, wherein the radial function Rn(ρ) is an even cosine function, which is expressed as:
R n ( ρ ) = { 1 n = 0 2 cos ( π n ρ ) n 0
where, ρ is a distance from an origin.
38. A content-based retrieval system for retrieving an image in a content-based image retrieval system including a web browser, a web server and a database storing images and image descriptors each of which represents characteristics of the image, the system comprising:
means for receiving a query image;
means for extracting a query image descriptor from the query image based on at least an angular component and a radial component of the query image;
means for requesting to retrieve an image based on the query image descriptor to the web server; and
means for receiving and displaying at least an image similar to the query image from the database.
39-74. (Cancelled)
Description
    FIELD OF THE INVENTION
  • [0001]
    The present invention relates to a content-based image retrieval system and a method for retrieving an image using the same; and, more particularly, to a content-based image retrieval system and a method for retrieving an image based on an angular radial transform (ART) image descriptor.
  • DESCRIPTION OF THE PRIOR ART
  • [0002]
    As Internet techniques have developed and use of multimedia data is increased in rapid, an image retrieval based on a text cannot guarantee reliability in results of the retrieval. To solve the problem as mentioned above, an image retrieval based on an image is performed.
  • [0003]
    The image retrieval based on the image means a method for finding an image (or images) similar to a query image by extracting an image descriptor describing a characteristic of the image from the image; and measuring a similarity between an image descriptor of the query image inputted by the user and that of an image stored on a database. The image descriptor includes a color descriptor, a texture descriptor and a shape descriptor, which respectively describes a color of the image, a texture of the image and a shape of the image. An efficiency of the image retrieval system depends on how much image descriptor efficiently describes characteristics of the image.
  • [0004]
    A moment descriptor is mostly used as a conventional shape descriptor. The moment descriptor is invariant to a size, a movement and a rotation of the image.
  • [0005]
    To obtain the moment descriptor of the input image, first, an edge extraction is processed. In other words, an object of the image is separated from a background. The image data is converted to binary data. Then, an outer boundary line of the object is extracted from the separated background and a shape vector of the object is obtained from the separated object.
  • [0006]
    In order to measure a similarity between the input image and an image stored on a database, a Euclidean distance measurement method is used. The Euclidean distance measurement method is expressed as following equation (1). D ( q , t ) = ( H q - H t ) T ( H q - H t ) = m = 0 M ( H q [ m ] - H t [ m ] ) ( 1 )
  • [0007]
    where, q is an input image, t is an image stored on a database, Hq is a moment value of the input image q, Ht is a moment value of the image stored on the database and M is an integer number between 0 and 6.
  • [0008]
    In the conventional content-based image retrieval system based on the moment descriptor, since the polynomial function used as a basis function is not orthogonal, extracted moment values, which are descriptors, are overlapped. Accordingly, an efficiency of the descriptor is low, and the descriptor cannot represent characteristics of the image, which are recognized by a user. Accordingly, the conventional content-based image retrieval system has a serious problem in that it cannot retrieve a similar image.
  • [0009]
    In order to solve the problem as mentioned above, some content-based retrieval systems based on a Zernike moment are developed. One of them is described in a pending U.S. patent application Ser. No. 09/203,569 filed on Dec. 2, 1998, “Method for Automatic Retrieval of Device-Mark Type Trademark Images Based upon Content of Trademark”.
  • [0010]
    The Zernike moment has an orthogonal value, however, may not effectively represent characteristics of the image in a radial direction. Accordingly, the conventional content-based image retrieval system based on the Zernike moment cannot perform an accurate image retrieval.
  • SUMMARY OF THE INVENTION
  • [0011]
    Therefore, it is an object of the present invention to provide a content-based image retrieval system and a method for retrieving image using the same, which are possible to search more similar image to a query image within a shorter time.
  • [0012]
    In accordance with an aspect of the present invention in order to obtain the object, there is provided a method for constructing a database storing images and image descriptors representing characteristics of the images, the method comprising the steps of: a) receiving an image; b) extracting an image descriptor from the image based on at least an angular component and a radial component of the image; c) storing the image on an image database; and d) storing the image descriptor on an image descriptor database.
  • [0013]
    In accordance with another aspect of the present invention, there is provided a method for retrieving an image in a content-based image retrieval system including a web browser, a web server and a database storing images and image descriptors each of which represents characteristics of the image, the method comprising the steps of: a) receiving a query image; b) requesting to retrieve an image based on a query image descriptor to the web server, the query image descriptor being extracted from the query image based on at least an angular component and a radial component of the query image; and c) receiving and displaying at least an image similar to the query image from the database.
  • [0014]
    In accordance with further another aspect of the present invention, there is provided a method for retrieving an image in a content-based image retrieval system including a web browser, a web server and a database storing images and image descriptors each of which represents characteristics of the image, the method comprising the steps of: a) receiving a query image from the web browser; b) extracting a query image descriptor from the query image based on at least an angular component and a radial component of the query image; c) comparing the query image descriptor with a plurality of image descriptors stored on the database, wherein the image descriptor is based on at least an angular component and a radial component of the image; d) arranging the image descriptors in order of a similarity to the query image descriptors; and e) allowing the database to provide at least an image similar to the query image to the web browser.
  • [0015]
    In accordance with still further another aspect of the present invention, there is provided a method for retrieving an image from a database storing images and image descriptors representing characteristics of the images, the method comprising the steps of: a) receiving a query image; b) extracting a query image descriptor from the query image based on at least an angular component and a radial component of the query image; c) comparing the query image descriptor with an image descriptor stored on the database; and d) determining a degree of a similarity between the query image descriptor and the image descriptor stored on the database.
  • [0016]
    In accordance with still another aspect of the present invention, there is provided a method for retrieving an image from a database storing images and image descriptors representing characteristics of the images, the method comprising the steps of: a) receiving a query image; b) extracting a query image descriptor from the query image based on at least an angular component and a radial component of the query image; c) comparing the query image descriptor with an image descriptor stored on the database; and d) determining a degree of a similarity between the query image descriptor and the image descriptor stored on the database.
  • [0017]
    In accordance with still another aspect of the present invention, there is provided data stream for use in retrieving an image, the data stream transmitted from a web browser to a web server, comprising: a retrieval request signal; and an image descriptor extracted from an image based on an angular component and a radial component of the image.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • [0018]
    The above and other objects and features of the instant invention will become apparent from the following description of preferred embodiments taken in conjunction with the accompanying drawings, in which:
  • [0019]
    [0019]FIG. 1 is a block diagram of a content-based image retrieval system in accordance with the present invention;
  • [0020]
    [0020]FIG. 2 is a flow chart illustrating a content-based image retrieval method in accordance with the present invention;
  • [0021]
    [0021]FIG. 3 is a flow chart illustrating a database construction process of FIG. 2;
  • [0022]
    [0022]FIG. 4 shows a set of ART basis functions in accordance with the present invention; and
  • [0023]
    [0023]FIG. 5 depicts an exemplary diagram of classified images in accordance with the present invention.
  • PREFERRED EMBODIMENT OF THE INVENTION
  • [0024]
    Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.
  • [0025]
    Referring to FIG. 1, a content-based image retrieval system includes a web browser, a web server and a database server.
  • [0026]
    The database server includes an image input unit 100, an image descriptor extracting unit 101, an image database 102 and an image descriptor database 103. The image input unit 100 receives images in order to construct the image database 102 and the image descriptor database 103. The image descriptor extracting unit 101 extracts an angular radial transform (ART) image descriptor of the image received by the image input unit 100. The image database 102 stores a plurality of images received through the image input unit 100. The image descriptor database 103 stores a plurality of image descriptors of the images extracted in the image descriptor extracting unit 101, which are respectively linked to corresponding to the image. In other words, the image descriptor is linked to the image.
  • [0027]
    The web browser includes a query image input unit 104 and an image output unit 107. The query image input unit 104 receives a query image to be retrieved from a user and transmits the query image to a query image descriptor extracting unit 105 in the web server.
  • [0028]
    The query image descriptor extracting unit 105 extracts an image descriptor from the query image received from the query input unit 104. The image descriptor comparing unit 106 receives the image descriptor of the query image from the query image descriptor extracting unit 105 and compares the image descriptor of the query image with the image descriptor stored on the image descriptor database 103 in the database server, thereby determining a degree of similarity between the image descriptor of the query image and the stored image descriptor. After comparison between the image descriptor of the query image and all of the image descriptors stored on the image descriptor database, at least an image similar to the query image is received from the image database 102 and outputted in the image output unit 107.
  • [0029]
    In this embodiment, a shape descriptor, in more particular, an ART shape descriptor is used as an image descriptor for the content-based image retrieval. In other words, absolute values of a predetermined number of ART coefficients are used as the image descriptor.
  • [0030]
    The ART has a rotation invariance of the image, which is necessary for the content-based image retrieval. The rotation invariance to of the image means that the image descriptor has the same value when the image is rotated.
  • [0031]
    The ART is defined as following equation (2). F n m = < V n m ( ρ , θ ) , f ( ρ , θ ) > = 0 2 π 0 1 V n m * ( ρ , θ ) , f ( ρ , θ ) ρ ( 2 )
  • [0032]
    where, Fnm is an ART coefficient of order n and m, n and m are integer numbers, Vnm(ρ,θ) is an ART basis function, ƒ(ρ,θ) is an image in polar coordinates, and * is a conjugate complex number.
  • [0033]
    The ART basis function Vnm(ρ,θ) is separable along the angular and the radial directions, which is expressed as following equation (3).
  • V nm(ρ,θ)=A m(θ)R n(ρ)   ( 3)
  • [0034]
    where, Am(θ) is an angular function and Rn(ρ) is a radial function.
  • [0035]
    The angular function Am(θ) is expressed as following equation (4). A m ( θ ) = 1 2 π exp ( j m θ ) ( 4 )
  • [0036]
    The ART coefficient (see, the equation (2)) uses in a polar coordinate (ρ,θ) instead of a rectangular coordinate (x, y) in order to obtain the rotation invariance. The polar coordinate is expressed by a distance ρ from the origin and an angle θ from the x-axis.
  • [0037]
    The radial function Rn(ρ) includes some types. One of them is ART-C type radial function expressed by equation (5) as following. ART - C : R n C ( ρ ) = { 1 n = 0 2 cos ( π n ρ ) n 0 ( 5 )
  • [0038]
    The ART-C type ART basis function set is illustrated in FIG. 4.
  • [0039]
    The ART coefficient Fnm obtained by the equation (2) are a series of complex numbers. In this specification, the shape descriptor is defined as a vector of an absolute value of the ART coefficient Fnm as following.
  • SD={∥Fnm∥}
  • [0040]
    where, n=0, 1, 2, . . . , k and m=0, 1, 2, . . . , l.
  • [0041]
    The ART coefficient extracted from an original image represents how much the original image has the ART basis function component. Accordingly, a multiplication of the ART coefficient by the ART basis function restores the original image. In theory, combinations of infinite ART basis functions are necessary for obtaining the original image. However, in real, an approximate image to the original image can be obtained by combinations of only twenty to thirty ART basis functions (see, FIG. 5). In other words, the image can be expressed by twenty to thirty numbers, which means that the ART coefficient is a considerably-efficient descriptor.
  • [0042]
    The ART basis function is orthogonal as can be seen from equation (7). 0 2 π 0 1 V n m ( ρ , θ ) , V n m * ( ρ , θ ) ρ = δ ( n - n , m - m ) ( 7 )
  • [0043]
    where, δ is a Kronecker delta function which is 0 in case of n=n′ and m=m′ and 0 in the other cases.
  • [0044]
    The ART coefficient has the rotation invariance as can be seen from equation (8).
  • ƒα(ρ,θ)=ƒ(ρ,α+θ)   (8)
  • [0045]
    ƒα(ρ,θ) is an image rotated by an angle α from the original image ƒ(ρ,θ).
  • [0046]
    The ART coefficient extracted from the rotated image ƒα(ρ,θ) can be obtained from equation (9) as following. F n m α = 0 2 π 0 1 V n m * ( ρ , θ ) , f α ( ρ , θ ) ρ ( 9 )
  • [0047]
    where, Fnm α is an ART coefficient extracted from the rotated image ƒα(ρ,θ).
  • [0048]
    A relation between the image ƒ(ρ,θ) and the rotated image ƒα(ρ,θ) is expressed as following equation (10).
  • F nm α =F nm exp(−jmα)   (10)
  • [0049]
    where, Fnm and Fnm α are the ART coefficient extracted from ƒ(ρ,θ) and ƒα(ρ,θ).
  • [0050]
    An absolute value of Fnm α is equal to the absolute value of Fnm, which is expressed by equation (11).
  • ∥Fnm α∥=∥Fnm∥  (11)
  • [0051]
    Dissimilarity between the query image and the image in the database is expressed as following equation (12). D = i w i S i q - S i r ( 12 )
  • [0052]
    where D is dissimilarity between the query image and the image in the database, wi is a constant coefficient, Si q is the i-th image descriptor of the query image, Si r the i-th image descriptor of the image in the database.
  • [0053]
    Hereinafter, a content-based image retrieval method using the ART image descriptor will be described in detail.
  • [0054]
    [0054]FIG. 2 is a flow chart illustrating a content-based image retrieval method in accordance with the present invention.
  • [0055]
    First, at step S200, the image descriptor database 103 and the image database 102 are constructed based on information inputted through the image input unit 100 and the image descriptor extracting unit 101.
  • [0056]
    A query image is received in the query image input unit 104 from a user at step S202. The query image input unit 104 provides three types of input method. One is that the user is allowed to directly draw the query image by using an input device, e.g., a mouse or a digitizer. Another is that the user is allowed to select one of prototype images provided by the web server. Another is that the user is allowed to select one of images stored on a storage device, e.g., a hard disk, a floppy disk or a CD-ROM.
  • [0057]
    Then, an image descriptor of the query image are extracted and transmitted to the image descriptor comparing unit 106 in the query image descriptor extracting unit 105 at step S204. The image descriptor of the query image is compared with the image descriptors stored on the database, at step S206, thereby calculating similarities between the query image and the images stored on the database. Images corresponding to the image descriptors, which are determined as similar to the image descriptor of the query image, are obtained from the image database 102, arranged in order of the similarity and transmitted to the image output unit 107 at step S208. The retrieved image(s), at least an image similar to the query image, is outputted through the image output unit 107 at step S210.
  • [0058]
    Here, the retrieved image may be reused as a prototype image. The user can modify the prototype image and request to retrieve again by using the modified prototype image as the query image.
  • [0059]
    Sample images are provided to the user as prototype images through the image output unit 107 at initial connection to the server. If the user selects one of the prototype images, the selected one is transmitted to the query image input unit 104.
  • [0060]
    [0060]FIG. 3 is a flow chart illustrating a database construction process of FIG. 2.
  • [0061]
    The image to be stored on the database is inputted through the image input unit 100 at step S300. The image descriptor of the image are extracted from the image at step S302 and the image is stored onto the image database 102 through the image input unit 100 at step S304. The extracted image descriptor corresponding to the image is stored onto the image descriptor database 103 at step 306.
  • [0062]
    [0062]FIG. 4 shows a set of ART basis functions in accordance with the present invention.
  • [0063]
    Referring to FIG. 4, a set of ART-C type ART basis functions expressed by the equation (5) is illustrated. The reference number n denotes a distance from the origin and m does an angle from the x-axis.
  • [0064]
    [0064]FIG. 5 depicts an exemplary diagram of classified images in accordance with the present invention.
  • [0065]
    The image similar to the query image is restored by using the equation (2) representing the ART definition equation.
  • [0066]
    Numbers of FIG. 5 denote the numbers of combined ART coefficients. As can be seen, as the numbers of the ART definition equations combined are increased, more similar image to the query image becomes to be combined.
  • [0067]
    In the content-based image retrieval system and method for retrieving image using the same as mentioned above, since the ART coefficients using the orthogonal basis function are utilized as an image descriptor, the image descriptor has a rotation invariance and no repetition of information. Since the ART descriptor used in the present invention effectively describes the angular and the radial directions of the image, thereby representing the image close to visual characteristics of human beings. Similar images to the query image can be rapidly and accurately retrieved. Also, either the query image inputted by the user or the retrieved image is used as the prototype image, thereby retrieving images in detail.
  • [0068]
    Although the preferred embodiments of the invention have been disclosed for illustrative purpose, those skilled in the art will be appreciate that various modifications, additions and substitutions are possible, without departing from the scope and spirit of the invention as disclosed in the accompanying claims.
Patent Citations
Cited PatentFiling datePublication dateApplicantTitle
US4747147 *Jun 16, 1986May 24, 1988Sparrow Malcolm KFingerprint recognition and retrieval system
US5465353 *Apr 1, 1994Nov 7, 1995Ricoh Company, Ltd.Image matching and retrieval by multi-access redundant hashing
US5684999 *Dec 2, 1994Nov 4, 1997Matsushita Electric Industrial Co., Ltd.Apparatus and a method for retrieving image objects based on correlation with natural language sentence parameters
US5893095 *Mar 28, 1997Apr 6, 1999Virage, Inc.Similarity engine for content-based retrieval of images
US6016487 *Mar 26, 1997Jan 18, 2000National Research Council Of CanadaMethod of searching three-dimensional images
Referenced by
Citing PatentFiling datePublication dateApplicantTitle
US7202867Jan 31, 2003Apr 10, 2007Microsoft CorporationGeneration of glow effect
US7242408Aug 19, 2005Jul 10, 2007Microsoft CorporationGraphical processing of object perimeter information
US7274365 *Jan 31, 2003Sep 25, 2007Microsoft CorporationGraphical processing of object perimeter information
US7411592Aug 19, 2005Aug 12, 2008Microsoft CorporationGraphical processing of object perimeter information
US7414625Nov 30, 2006Aug 19, 2008Microsoft CorporationGeneration of glow effect
US7970171Jan 18, 2007Jun 28, 2011Ricoh Co., Ltd.Synthetic image and video generation from ground truth data
US7991778Jul 31, 2006Aug 2, 2011Ricoh Co., Ltd.Triggering actions with captured input in a mixed media environment
US8005831Jul 31, 2006Aug 23, 2011Ricoh Co., Ltd.System and methods for creation and use of a mixed media environment with geographic location information
US8073263Oct 7, 2008Dec 6, 2011Ricoh Co., Ltd.Multi-classifier selection and monitoring for MMR-based image recognition
US8086038Jul 11, 2007Dec 27, 2011Ricoh Co., Ltd.Invisible junction features for patch recognition
US8144921Jul 11, 2007Mar 27, 2012Ricoh Co., Ltd.Information retrieval using invisible junctions and geometric constraints
US8156115Mar 31, 2008Apr 10, 2012Ricoh Co. Ltd.Document-based networking with mixed media reality
US8156116Dec 23, 2008Apr 10, 2012Ricoh Co., LtdDynamic presentation of targeted information in a mixed media reality recognition system
US8156427Jul 31, 2006Apr 10, 2012Ricoh Co. Ltd.User interface for mixed media reality
US8176054Jul 12, 2007May 8, 2012Ricoh Co. LtdRetrieving electronic documents by converting them to synthetic text
US8184155Jul 11, 2007May 22, 2012Ricoh Co. Ltd.Recognition and tracking using invisible junctions
US8195659Jul 31, 2006Jun 5, 2012Ricoh Co. Ltd.Integration and use of mixed media documents
US8201076Oct 17, 2008Jun 12, 2012Ricoh Co., Ltd.Capturing symbolic information from documents upon printing
US8276088Jul 11, 2007Sep 25, 2012Ricoh Co., Ltd.User interface for three-dimensional navigation
US8332401Jul 31, 2006Dec 11, 2012Ricoh Co., LtdMethod and system for position-based image matching in a mixed media environment
US8335789Jul 31, 2006Dec 18, 2012Ricoh Co., Ltd.Method and system for document fingerprint matching in a mixed media environment
US8369655Sep 29, 2008Feb 5, 2013Ricoh Co., Ltd.Mixed media reality recognition using multiple specialized indexes
US8385589Feb 26, 2013Berna ErolWeb-based content detection in images, extraction and recognition
US8385660Jun 24, 2009Feb 26, 2013Ricoh Co., Ltd.Mixed media reality indexing and retrieval for repeated content
US8489987Nov 5, 2008Jul 16, 2013Ricoh Co., Ltd.Monitoring and analyzing creation and usage of visual content using image and hotspot interaction
US8510283 *Sep 15, 2008Aug 13, 2013Ricoh Co., Ltd.Automatic adaption of an image recognition system to image capture devices
US8521737Jul 31, 2006Aug 27, 2013Ricoh Co., Ltd.Method and system for multi-tier image matching in a mixed media environment
US8600989Jul 31, 2006Dec 3, 2013Ricoh Co., Ltd.Method and system for image matching in a mixed media environment
US8676810Sep 29, 2008Mar 18, 2014Ricoh Co., Ltd.Multiple index mixed media reality recognition using unequal priority indexes
US8825682Sep 15, 2008Sep 2, 2014Ricoh Co., Ltd.Architecture for mixed media reality retrieval of locations and registration of images
US8838591Jul 31, 2006Sep 16, 2014Ricoh Co., Ltd.Embedding hot spots in electronic documents
US8856108Sep 15, 2008Oct 7, 2014Ricoh Co., Ltd.Combining results of image retrieval processes
US8868555Sep 15, 2008Oct 21, 2014Ricoh Co., Ltd.Computation of a recongnizability score (quality predictor) for image retrieval
US8949287Jul 31, 2006Feb 3, 2015Ricoh Co., Ltd.Embedding hot spots in imaged documents
US8989431Mar 31, 2008Mar 24, 2015Ricoh Co., Ltd.Ad hoc paper-based networking with mixed media reality
US9020966 *Dec 19, 2008Apr 28, 2015Ricoh Co., Ltd.Client device for interacting with a mixed media reality recognition system
US9058331Jul 27, 2011Jun 16, 2015Ricoh Co., Ltd.Generating a conversation in a social network based on visual search results
US9063952Oct 7, 2008Jun 23, 2015Ricoh Co., Ltd.Mixed media reality recognition with image tracking
US9063953Mar 8, 2010Jun 23, 2015Ricoh Co., Ltd.System and methods for creation and use of a mixed media environment
US9171202Jul 31, 2006Oct 27, 2015Ricoh Co., Ltd.Data organization and access for mixed media document system
US9176984Oct 17, 2008Nov 3, 2015Ricoh Co., LtdMixed media reality retrieval of differentially-weighted links
US20060029246 *Oct 4, 2005Feb 9, 2006Boesen Peter VVoice communication device
US20070030523 *Aug 2, 2005Feb 8, 2007Kabushiki Kaisha ToshibaSystem and method for identifying a submitter of a printed or scanned document
US20090074300 *Sep 15, 2008Mar 19, 2009Hull Jonathan JAutomatic adaption of an image recognition system to image capture devices
US20090100050 *Dec 19, 2008Apr 16, 2009Berna ErolClient device for interacting with a mixed media reality recognition system
US20110081892 *Sep 10, 2010Apr 7, 2011Ricoh Co., Ltd.System and methods for use of voice mail and email in a mixed media environment
WO2015155628A1 *Mar 29, 2015Oct 15, 2015Eyeways Systems Ltd.Apparatus and method for image-based positioning, orientation and situational awareness
Classifications
U.S. Classification1/1, 707/E17.024, 707/999.1
International ClassificationG06T1/00, G06T7/00, G06F17/30, G06K9/52
Cooperative ClassificationY10S707/99936, Y10S707/99943, Y10S707/99933, Y10S707/99932, Y10S707/99934, Y10S707/99935, G06F17/30259, G06K9/52, G06K9/4609
European ClassificationG06K9/52, G06F17/30M1S, G06K9/46A1