WO2013129729A1 - Système de recherche d'image de réalité augmentée en temps réel à l'aide d'un descripteur de mise en page et d'un point de caractéristique d'image - Google Patents

Système de recherche d'image de réalité augmentée en temps réel à l'aide d'un descripteur de mise en page et d'un point de caractéristique d'image Download PDF

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Publication number
WO2013129729A1
WO2013129729A1 PCT/KR2012/002533 KR2012002533W WO2013129729A1 WO 2013129729 A1 WO2013129729 A1 WO 2013129729A1 KR 2012002533 W KR2012002533 W KR 2012002533W WO 2013129729 A1 WO2013129729 A1 WO 2013129729A1
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Prior art keywords
image
layout
unit
feature point
descriptor
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Ceased
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PCT/KR2012/002533
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English (en)
Korean (ko)
Inventor
이재영
온기원
안기영
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K3I CO Ltd
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K3I CO Ltd
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/583—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/20—Scenes; Scene-specific elements in augmented reality scenes
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
    • G06V30/40—Document-oriented image-based pattern recognition
    • G06V30/41—Analysis of document content
    • G06V30/412—Layout analysis of documents structured with printed lines or input boxes, e.g. business forms or tables
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
    • G06V30/40—Document-oriented image-based pattern recognition
    • G06V30/41—Analysis of document content
    • G06V30/418—Document matching, e.g. of document images

Definitions

  • the present invention relates to a real-time augmented reality image retrieval system using a layout descriptor and an image feature point, more specifically, to extract a desired page from a PDF file of a print medium, a newspaper, etc., which is a target of an augmented reality service efficiently
  • a layout descriptor matches by using a layout descriptor, and matches by using image feature point vectors within a limited page range and augments it from a document image management server under a mobile terminal and a network environment.
  • an e-book refers to a digital book that is produced through XML, digital images, multimedia, etc., rather than a book printed on paper, and viewed through terminal screens such as computers, PDAs, and mobile phones.
  • Second-generation e-books that combine multimedia such as PDF, XML, and first generation e-books have been actively developed. It has been in the spotlight as a means to replace paper books.
  • Marker-based techniques are capable of page recognition and tracking, but there is a problem in that the content is not augmented when a part of the marker is obscured, as well as attaching a marker of a specific pattern to the printed publication.
  • an object of the present invention is to efficiently detect a desired page from a database stored in a PDF file extracted from a print medium, a newspaper, etc., which is an object of an augmented reality service.
  • a desired page from a database stored in a PDF file extracted from a print medium, a newspaper, etc.
  • an augmented reality service which is an object of an augmented reality service.
  • it is matched by using a layout descriptor, and it is matched by using the image feature point vector within the limited page range from the document image management server under the mobile terminal and the network environment. It is to be able to search the page surface of the augmented reality service.
  • XML layout descriptor XML
  • It includes the image information DB that stores the layout descriptor item and the image feature point vector information, and searches for the image in the image information DB by referring to the layout descriptor XML provided when the image is requested from the mobile terminal.
  • FIG. 1 is an overall configuration diagram of a real-time augmented reality image retrieval system using a layout descriptor and image feature points according to an embodiment of the present invention.
  • FIG. 2 is a block diagram of a mobile terminal of a real-time augmented reality image retrieval system using a layout descriptor and image feature points according to an embodiment of the present invention.
  • FIG. 3 is a block diagram of a document image management server of a real-time augmented reality image retrieval system using a layout descriptor and image feature points according to an embodiment of the present invention.
  • FIG. 4 is a block diagram of an image information DB construction unit of a real-time augmented reality image retrieval system using a layout descriptor and image feature points according to an exemplary embodiment of the present invention.
  • FIG. 5 is a flowchart illustrating an augmented reality of a real-time augmented reality image retrieval system using a layout descriptor and an image feature point according to an embodiment of the present invention.
  • FIG. 6 is a flowchart illustrating a flow of storing information in an image information DB of a real-time augmented reality image retrieval system using a layout descriptor and an image feature point according to an embodiment of the present invention.
  • FIG. 7 is an exemplary diagram illustrating a data field of an image information DB of a real-time augmented reality image retrieval system using a layout descriptor and image feature points according to an embodiment of the present invention.
  • FIG. 8 is an exemplary diagram illustrating an example of converting a PD file to an image of a real-time augmented reality image retrieval system using a layout descriptor and an image feature point according to an embodiment of the present invention.
  • FIG. 9 is an exemplary view showing the entire page layout of a real-time augmented reality image search system using a layout descriptor and image feature points according to an embodiment of the present invention.
  • FIG. 10 is an exemplary diagram illustrating a layout descriptor XML of a real-time augmented reality image retrieval system using a layout descriptor and image feature points according to an embodiment of the present invention.
  • FIG. 1 is an overall configuration diagram of a real-time augmented reality image retrieval system using a layout descriptor and image feature points according to an embodiment of the present invention.
  • a real-time augmented reality image retrieval system using a layout descriptor and an image feature point is provided.
  • XML layout descriptor XML
  • It includes the image information DB that stores the layout descriptor item and the image feature point vector information, and searches for the image in the image information DB by referring to the layout descriptor XML provided when the image is requested from the mobile terminal.
  • the mobile terminal processes the query request query image to form a block and records the layout descriptor as XML.
  • the layout descriptor XML includes the total number of blocks, the number of blocks for each central reference position, the number and positions of separators, and the like.
  • the document image management server parses the layout descriptor XML content as a database inquiry condition and performs the inquiry.
  • a plurality of pages may be retrieved as a result of the matching, and the image feature point matching operation is performed within the retrieved page range, and the page having the highest similarity is presented to the mobile terminal as a recognition result.
  • FIG. 2 is a block diagram of a mobile terminal of a real-time augmented reality image retrieval system using a layout descriptor and image feature points according to an embodiment of the present invention.
  • the mobile terminal 100 of the present invention As shown in Figure 2, the mobile terminal 100 of the present invention,
  • An image capture unit 110 for capturing an image obtained from a camera
  • An image preprocessing unit 120 for acquiring the captured image and performing preprocessing of downsampling, noise removal, and tilt correction;
  • An image feature point extracting unit 130 for extracting a feature point by acquiring an image having undergone a preprocessing process by the image preprocessing unit;
  • a layout block generator 140 for generating a layout block by setting a distance between adjacent pixels of an image as a threshold value
  • An image feature point vector converter 150 for acquiring an image feature point extracted by the image feature point extractor and converting the image feature point into a vector
  • An image lookup request unit 170 for acquiring an image feature point vector converted by the image feature point vector converting unit and a layout descriptor XML generated by the layout descriptor XMl generation unit and requesting an image search to a document image management server; ,
  • Tracking module unit 180 for tracking the three-dimensional coordinates on the image page sent from the document image management server,
  • the image capture unit 110 is to capture an image in a continuous frame from the camera.
  • the image preprocessing unit 120 acquires the captured image and performs preprocessing such as downsampling, noise removal, and tilt correction.
  • the characteristic parts of the present invention are the feature point extraction and feature point vector transformation and layout block generation and layout descriptor XML generation.
  • the image feature point extractor 130 obtains an image that has been preprocessed by the image preprocessing unit and extracts feature points, and the layout block generator 140 sets distances between adjacent pixels of the image based on a threshold value. To create the layout block.
  • the image feature point vector converter 150 acquires the image feature points extracted by the image feature point extractor and converts the image feature points into a vector.
  • the layout descriptor X-Mn generator 160 generates a layout generated by the layout block generator.
  • the layout descriptor XML (XML) is generated from the block.
  • the image lookup request unit 170 obtains the image feature point vector converted by the image feature point vector converting unit and the layout descriptor XML generated by the layout engineer XML generation unit to obtain a document image management server. You will be asked to retrieve an image.
  • the tracking module unit 180 tracks the three-dimensional coordinates on the image page sent from the document image management server, and performs rendering with reference to the three-dimensional coordinates tracked from the tracking module unit by the rendering module unit 190. To provide augmented reality information.
  • FIG. 3 is a block diagram of a document image management server of a real-time augmented reality image retrieval system using a layout descriptor and image feature points according to an embodiment of the present invention.
  • the document image management server 200 As shown in Figure 3, the document image management server 200,
  • Parsing unit 210 for parsing in order to obtain the layout descriptor XML transmitted to the image information request from the mobile terminal to convert the image information DB query conditions
  • a matching result list creating unit 220 for searching an image corresponding to the layout condition from the image information DB and creating a layout matching result list
  • An image matching query unit 230 for retrieving an image feature point vector transmitted from the mobile terminal and retrieving an image matching the image feature point vector from a layout matching result list created by the matching result list creating unit;
  • An image information DB 240 for storing and managing an original storage path, an image storage path, a layout descriptor item, and image feature point vector information;
  • An image transmitting unit 250 for transmitting an image queried by the image matching inquiry unit to a mobile terminal
  • the parsing unit 210 acquires the layout descriptor XML (XML) transmitted when the image inquiry request is received from the mobile terminal and parses it to convert the image information into the DB information retrieval condition.
  • XML layout descriptor XML
  • the matching result list creating unit 220 inquires an image matching the layout condition from the image information DB 240 and creates a layout matching result list.
  • the image matching query unit 230 obtains an image feature point vector to be sent and searches an image matching the image feature point vector in the layout matching result list created by the matching result list creating unit.
  • the characteristic is that if an image with similarity rate above the threshold is obtained, the search result is sent to the image transmitter. If an image with a similarity rate below the threshold is obtained, another image is obtained. It performs a matching operation on the image.
  • the image transmitting unit 250 transmits the image inquired by the image matching inquiry unit to the mobile terminal, and the mobile terminal tracks and renders the image.
  • FIG. 4 is a block diagram of an image information DB construction unit of a real-time augmented reality image retrieval system using a layout descriptor and image feature points according to an exemplary embodiment of the present invention.
  • the image information DB construction unit 270 of the present invention extracts the layout descriptor item and the image feature point vector information from the original image file and stores the extracted information in the image information DB.
  • the image information DB building unit 270 Specifically, the image information DB building unit 270,
  • An image blocker 272 for acquiring an image converted by the image converter and forming a block
  • An adjacent block integrating unit 273 for integrating into one block when the vertical distance between the image blocks formed by the image blocking unit is less than or equal to a threshold;
  • a layout descriptor extracting unit 274 for extracting a layout descriptor describing a relative position of each block based on the entire layout obtained by the image block forming unit and the adjacent block integrating unit;
  • An invariant coordinate system conversion unit 276 for acquiring image information obtained by performing the preprocessing and feature point extraction and converting the image information into an invariant coordinate system
  • a DB building module unit 278 for generating a hash table by acquiring an image ID, an original storage path, an image storage path, layout descriptor items, and image feature point vector information, and storing the image in an image information DB.
  • the image conversion unit 271 converts the PD file into an image, as shown in FIG. 8, and the PD file is individually given per page.
  • the image blocker 272 forms a block by acquiring an image converted by the image converter.
  • the adjacent block integrating unit 273 merges into one block when the vertical distance between the image blocks formed by the image block forming unit is less than or equal to the threshold.
  • the layout descriptor extracting unit 274 extracts a layout descriptor describing a relative position of each block based on the entire layout obtained by the image block forming unit and the adjacent block integrating unit.
  • the number of blocks on the left and right and the quadrant position of the separator between paragraphs are extracted based on the middle of the page, and these attributes are used as an index of the database.
  • the feature storing point extractor 275 for storing the image is obtained by converting the image converted by the image converter 271 to perform presampling of downsampling, noise removal, and tilt correction, and extracts feature points from the preprocessing image. Done.
  • the feature point extraction generates a blurred image using a binary image generation and a Gaussian filter, and extracts the center of each of the resulting word regions as a feature point.
  • the invariant coordinate system conversion unit 276 obtains image information obtained by performing a preprocessing process and feature point extraction and converts the image information into a invariant coordinate system.
  • the cross ratio between two triangles connecting four adjacent points is calculated to represent invariant relations between adjacent points.
  • the cross ratio is calculated by combining all adjacent points.
  • the hash index calculation unit 277 calculates a hash index by obtaining image information obtained by performing a preprocessing process and feature point extraction.
  • a hash scheme is adopted for fast searching.
  • the DB building module unit 278 acquires an image ID, an original storage path, an image storage path, layout descriptor items, and image feature point vector information, generates a hash table, and stores the hash table in the image information DB. See FIG. 7)
  • FIG. 5 is a flowchart illustrating an augmented reality of a real-time augmented reality image retrieval system using a layout descriptor and an image feature point according to an embodiment of the present invention.
  • the image capture unit 110 captures an image obtained from a camera (S100), and the image preprocessing unit 120 acquires the captured image to downsample, remove noise, and correct the tilt.
  • the pretreatment process is performed (S110).
  • the image feature point extractor 130 obtains an image that has been preprocessed by the image preprocessing unit to extract the feature point (S120), and the image feature point vector converter 150 is extracted by the image feature point extractor.
  • the image feature point is obtained and converted into a vector (S125).
  • the layout block generation unit 140 sets the distance between adjacent pixels of the image based on a threshold value to generate a layout block (S130), and the layout descriptor XM generation unit 160 generates the layout block by the layout block generation unit.
  • the layout descriptor XML (XML) is generated from the used layout block (S135).
  • the image lookup request unit 170 obtains the image feature point vector converted by the image feature point vector converting unit and the layout descriptor XML generated by the layout engineer XML generation unit, and requests an image inquiry to the document image management server. (S140) will be.
  • the parsing unit 210 of the document image management server 200 requests an image inquiry from the mobile terminal
  • the parsing unit 210 parses to obtain the layout descriptor XML that is sent and converts it into an image information DB inquiry condition (S150).
  • the matching result list creation unit 220 inquires an image matching the layout condition from the image information DB (S160) to create a layout matching result list (S170), and the image matching query unit 230 is sent from the mobile terminal.
  • an image matching the image feature point vector is searched in the layout matching result list created by the matching result list generator (S180).
  • the image matching inquiry unit 230 determines whether or not having similarity above the threshold value (S190), and obtains an image having similarity above the threshold value from the image transmitting unit and transmits it to the mobile terminal.
  • the tracking module 180 tracks the 3D coordinates on the image page (S200), and the rendering module 190 performs rendering by referring to the 3D coordinates tracked by the tracking module unit. (S210) to output the augmented reality information on the screen.
  • FIG. 6 is a flowchart illustrating a flow of storing information in an image information DB of a real-time augmented reality image retrieval system using a layout descriptor and an image feature point according to an embodiment of the present invention.
  • the image converter 271 converts the PD file to an image (S310).
  • the image blocker 272 acquires the image converted by the image converter to form a block (S350), and the adjacent block integrator 273 vertical distances between the image blocks formed by the image blocker. Is less than or equal to the threshold (S360) is integrated into one block, the layout descriptor extraction unit 274 is a layout for explaining the relative position of each block based on the overall layout obtained by the image block unit and the adjacent block integration unit A descriptor is extracted (S370).
  • the feature point extraction process should be performed in the conversion of the PD file into an image (S310).
  • the feature storing unit extractor 275 for storing the data acquires the image converted by the image converting unit 271 to perform preprocessing of downsampling, noise removal, and tilt correction, and then extracts the feature points from the preprocessing image.
  • the invariant coordinate system converter 276 acquires the image information obtained by performing the preprocessing and the feature point extraction, and converts the information into the invariant coordinate system S330.
  • the hash index calculation unit 277 obtains image information obtained by performing the preprocessing and feature point extraction to calculate a hash index (S340).
  • the DB building module unit 278 obtains an image ID, an original storage path, an image storage path, layout descriptor items, and image feature point vector information, generates a hash table, and stores the hash table in the image information DB.
  • the present invention extracts from a PDF file of a print medium, a newspaper, etc., which is an object of an augmented reality service, to efficiently detect a desired page in a stored database.
  • a layout descriptor may be used when searching the entire layout of a page.

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
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  • Library & Information Science (AREA)
  • Artificial Intelligence (AREA)
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PCT/KR2012/002533 2012-02-28 2012-04-04 Système de recherche d'image de réalité augmentée en temps réel à l'aide d'un descripteur de mise en page et d'un point de caractéristique d'image Ceased WO2013129729A1 (fr)

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KR1020120020018A KR101329102B1 (ko) 2012-02-28 2012-02-28 레이아웃 기술자와 이미지 특징점을 이용한 실시간 증강현실 이미지 검색시스템

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CN106126655A (zh) * 2016-06-27 2016-11-16 乐视控股（北京）有限公司 网页保存处理方法及装置
CN112269854A (zh) * 2020-11-18 2021-01-26 浙江大学 基于倒排索引的大规模数据相似特征检测方法
CN113743420A (zh) * 2021-08-26 2021-12-03 北京邮电大学 一种基于云边端协同的Web AR图像识别方法及系统

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CN113743420B (zh) * 2021-08-26 2023-12-05 北京邮电大学 一种基于云边端协同的Web AR图像识别方法及系统

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