EP1080425A1 - Structure de donnees de grille d'image a plusieurs niveaux et procede de recherche d'image utilisant cette structure - Google Patents

Structure de donnees de grille d'image a plusieurs niveaux et procede de recherche d'image utilisant cette structure

Info

Publication number
EP1080425A1
EP1080425A1 EP00902188A EP00902188A EP1080425A1 EP 1080425 A1 EP1080425 A1 EP 1080425A1 EP 00902188 A EP00902188 A EP 00902188A EP 00902188 A EP00902188 A EP 00902188A EP 1080425 A1 EP1080425 A1 EP 1080425A1
Authority
EP
European Patent Office
Prior art keywords
image
color
similarity
grid
grids
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Withdrawn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
EP00902188A
Other languages
German (de)
English (en)
Other versions
EP1080425A4 (fr
Inventor
Hyeon Jun Hansin Life Apt. KIM
Sung Bae Jun
Jin Soo Lee
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.)
LG Electronics Inc
Original Assignee
LG Electronics Inc
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 LG Electronics Inc filed Critical LG Electronics Inc
Publication of EP1080425A1 publication Critical patent/EP1080425A1/fr
Publication of EP1080425A4 publication Critical patent/EP1080425A4/fr
Withdrawn legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06F16/5838—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using colour

Definitions

  • the present invention relates to an image grid data structure and an image search method using the same, and in particular to a multilevel image grid data structure having a structure of different hierarchical grid levels with respect to one color feature related to a spatial color property of a still image and an image search method for searching an image using a multilevel image grid data structure
  • the importance of each feature is different in accordance with the characteristics of an image which will be searched
  • the importance is different for each cell in the conventional image grid data structure
  • a weight value reflecting the importance of each element can be determined as a different value for each element forming the n-dimensional structure
  • the average importance for elements of a certain feature is not useful, i.e , a predetermination of an average value for elements of a certain feature is not useful in image search since the importance of each element caries by a reference image of target image
  • the conventional image grid data structure is formed of only one level, the destination contained in an image (or target image) is not accurately searched in the conventional image search method
  • each level is expressed by the cells of a hierarchical structure of different levels by expressing one feature based on a multilevel image grid, and expressing a region representative color of each cell and a reliability with respect to the region representative color
  • a multilevel image data structure in which a spatial color feature of one image is expressed in a hierarchical image grid structure having more than two different levels
  • an image search method using a multilevel image data structure according to the present invention in which the color similarities of a spatial color feature of a reference image divided into different hierarchical image grid levels and a target image are matched, so that an image is searched in accordance with user's content-based query
  • Figure 1 is a view illustrating an embodiment of a multilevel image grid data structure and a 3-level image grid data structure according to the present invention
  • Figure 2 is a view illustrating an image search method using a multilevel image grid data structure and the construction of a match between 3-level image grid data structures according to the present invention
  • Figure 3 is a view illustrating an embodiment of an image search method using a multilevel image grid data structure and the construction of a match between the same levels in a 3-level image grid data structure according to the present invention
  • Figure 4 is a view illustrating an embodiment of an image search method using a multilevel image grid data structure and the construction of a match between different levels of a 3-level image grid data structure according to the present invention
  • Figures 5A and 5B are views illustrating an embodiment of an image search method using a multilevel image grid data structure according to the present invention, of which Figure 5A is a view illustrating two same image grid data structures, and Figure 5B is a view illustrating a process of a match of two image grid data structures
  • the present invention relates to a multilevel image grid data structure and an image search method using the same
  • the method for generating a multilevel image grid data structure according to the present invention will be explained
  • square image it is uniformly divided by height and width
  • one side is uniformly divided in accordance with an aspect ratio of a width and height of an image
  • the other side is uniformly divided by the unit of one side
  • a regular square structure having the same length of horizontal and vertical sides is divided by the same unit, and in the case of a rectangular structure having different lengths of horizontal and vertical sides, one s ⁇ de(for example, a lengthy side) is uniformly divided, and the other s ⁇ de(for example, a shorter side) is divided by the dividing
  • the spatial color feature is divided into hierarchical grids of different levels for thereby expressing a structure of a multilevel image grid
  • each image grid is a hierarchical structure of different levels, and the resolution of each level is hierarchically divided
  • the cell of each grid is assigned with two values which are a regional representative color (RRC) and a reliability score (S) relating to an accuracy of the regional representative color
  • RRC regional representative color
  • S reliability score
  • the first level image grid is the lowest
  • the second level image grid is an intermediate level
  • the third level image grid is higher than the second level image grid in accordance with the divided levels
  • the first level image grid is divided into the image region including a
  • M1xN1 number of local cells in proportion to the aspect ratio of a vertical side M and a horizontal side N
  • Each cell is expressed as a region representative color(RRC) which represents each region, and a reliability score(S) which corresponds to the accuracy of the representative color value
  • the second level image grid and the third level image grid are divided into the image regions including a M2xN2 number and M3xN3 number of local cells in accordance with the dividing state, and each cell has a region representative color(RRC) and a reliability score(S)
  • a certain cell Cell( ⁇ ) of the third level image grid is expressed as a region representative color and a reliability score C ⁇ ., S ⁇ ,,
  • the number of divisions of each of the image levels of 1 st level, second level and third level is determined based on an aspect ratio of the image for accurately expressing the position of the object included in the image Namely, in the case of the lengthy side, the lengthy side is uniformly divided, and the short side is divided by the divided unit of the lengthy side
  • the vertical and horizontal lengths may set identically
  • Different images divided into the multilevel image grids are expressed as a representative region color(RRC) which represents the region and a reliability score which expresses an accuracy of the representative color, and a pair of representative region color and reliability are matched to another one, and a cell similarity is computed in accordance with the content-based query of a user for thereby performing an image search
  • the color similarity between two images is computed using the multilevel image grid data structure by comparing the cells included in an image grid of each level and the region color(RRC) representing each cell Namely, the color similarity between two cells is computed using the color similarities Color_S ⁇ m(RRC_C1 , RRC_C2) which represent the similarity of a region representative color value between the cell C1 and Cell C2
  • the first weight ( ⁇ ) is multiplied by the color similarities
  • Figure 2 illustrates an embodiment of the image search using a multilevel image grid data structure according to the present invention and a similarity- based search between the grids of two images ⁇ and I2 having a 3-level image grid data structure
  • and I2 include first level image grids G1 ⁇ sr G2 - ) s t second level image grids G ⁇ 2nd- ⁇ 2 2nd' and tn ⁇ rd level ⁇ m ag e g ⁇ d s G-
  • , G2) between grid levels included in two images are compared between the levels
  • the similarities of two cells corresponding to the same levels of two different images are summed, and the similarities of two cells are summed to the thusly summed value by shifting in the horizontal and vertical directions by the aspect ratio At this time, the number of the matches of two grids is computed by adding 1 to the absolute value of the difference of the aspect ratio of a certain level of two images.
  • Equation 404 adapting Equation 404 to Equation 4-1 based on the aspect ratios M:N, O:P.
  • Equation 4-1 is applied when P is less than N and M is less than O and Equation 4-2 is applied when the length N of the grid Gi is shorter than length P of grid G2 and the width O of the grid G2 is shorter than width M of the grid G1
  • Equation 4-3 is applied when the vertical length P of the grid G2 is shorter than N of grid G1 and the horizontal length M of the grid G1 is shorter than O of G2
  • Equation 4-4 is applied when N of G-
  • the color region matching operation is performed for searching the region in which the representative color values are similar between the multilevel image grids
  • the search is performed based on a method for searching the color similarity from a translation position and a relative position between the grid level(Exact scale matching) of the same size, and a method for searching the color similarity from a translation position and the relative position between the grid levels( Inter-scale matching) of different sizes
  • the color region matching operation between the image grid levels(Exact scale matching) of the same size is performed based on a method for searching a color region of the same levels from a target image
  • the position is matched with the relative position based on the same image grid level of the target image, and then the similarity of the color region is computed, and the position is matched with a translation position at the same level of the target image for thereby computing a similarity of the color region
  • the color region matching operation between the different image grid levels(lnter-scale matching) is performed based on a method for searching the different level color regions among the target images, and a similarity of the color region of the same level is computed among the different image grid levels of the target image
  • the similarity of the color region is computed by matching the position with the same position among the different image grid levels of the target image, and the similarity of the color region is computed by matching the position with the translation position at another level of the target image
  • one image grid data structure is divided into multilevel grid data structures Therefore, it is possible to effectively response with respect to a subjective query by a user when searching a content-based image using the divided multilevel grid structures
  • an image search speed is fast and accurate under a certain condition

Landscapes

  • Engineering & Computer Science (AREA)
  • Library & Information Science (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Data Mining & Analysis (AREA)
  • Image Analysis (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Processing Or Creating Images (AREA)
  • Image Processing (AREA)
  • Color Image Communication Systems (AREA)

Abstract

La présente invention concerne un procédé de recherche d'image capable d'exprimer une caractéristique de couleur se rapportant à une caractéristique de couleur spatiale d'une image fixe s'appuyant sur une grille d'image à plusieurs niveau et la recherche d'image à base de similitude par utilisation de la grille d'image multiniveau ainsi exprimée. En l'occurrence, on génère des grilles hiérarchisées de différents niveaux par rapport à une caractéristique de façon à obtenir une structure de données dans laquelle chaque cellule correspondant à la grille s'exprime en fonction d'une fiabilité sur une couleur représentative d'une région et la couleur représentative de la région, si bien qu'il est possible de rechercher des images, rapidement et avec précision, en fonction d'une requête utilisateur à base de contenu, en s'appuyant sur une correspondance des cellules du même niveau que deux grilles d'images et différents niveaux ou une correspondance locale des couleurs de la concordance en grille.
EP00902188A 1999-02-01 2000-01-28 Structure de donnees de grille d'image a plusieurs niveaux et procede de recherche d'image utilisant cette structure Withdrawn EP1080425A4 (fr)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
KR9903184 1999-02-01
KR1019990003184A KR100319151B1 (ko) 1999-02-01 1999-02-01 다중레벨 이미지 데이터 생성 방법과 다중레벨 이미지 데이터를 이용한 이미지 검색방법
PCT/KR2000/000070 WO2000054181A1 (fr) 1999-02-01 2000-01-28 Structure de donnees de grille d'image a plusieurs niveaux et procede de recherche d'image utilisant cette structure

Publications (2)

Publication Number Publication Date
EP1080425A1 true EP1080425A1 (fr) 2001-03-07
EP1080425A4 EP1080425A4 (fr) 2002-05-29

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EP00902188A Withdrawn EP1080425A4 (fr) 1999-02-01 2000-01-28 Structure de donnees de grille d'image a plusieurs niveaux et procede de recherche d'image utilisant cette structure

Country Status (6)

Country Link
EP (1) EP1080425A4 (fr)
JP (1) JP3541011B2 (fr)
KR (1) KR100319151B1 (fr)
CN (1) CN1165859C (fr)
AU (1) AU2330600A (fr)
WO (1) WO2000054181A1 (fr)

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CN100346339C (zh) * 2002-11-20 2007-10-31 富士通株式会社 图像检索方法及图像检索装置
KR100609022B1 (ko) * 2004-06-09 2006-08-03 학교법인 영남학원 공간관계와 주석을 이용한 이미지 검색 방법
US7650345B2 (en) * 2005-02-28 2010-01-19 Microsoft Corporation Entity lookup system
CN102376088A (zh) * 2010-08-24 2012-03-14 康博公司 用于在计算上量化图像间相似性的系统
KR101284243B1 (ko) 2012-05-11 2013-07-09 주식회사 아시아정밀 미실장 인쇄회로기판 검사장치의 크로스 셰어 그리드
JP5894013B2 (ja) * 2012-05-30 2016-03-23 公益財団法人鉄道総合技術研究所 コンクリート表面の変状管理方法
CN104424230B (zh) * 2013-08-26 2019-10-29 阿里巴巴集团控股有限公司 一种网络商品推荐方法及装置
EP3274986A4 (fr) 2015-03-21 2019-04-17 Mine One GmbH Procédés, systèmes et logiciel pour 3d virtuelle
US10853625B2 (en) 2015-03-21 2020-12-01 Mine One Gmbh Facial signature methods, systems and software
US11550387B2 (en) 2015-03-21 2023-01-10 Mine One Gmbh Stereo correspondence search
KR102083619B1 (ko) * 2015-08-31 2020-03-03 오스템임플란트 주식회사 치아 교정 계획을 위한 이미지 처리 방법, 이를 위한 장치 및 기록 매체
CN106873931A (zh) * 2017-02-15 2017-06-20 北京佳格天地科技有限公司 栅格数据可视化装置、方法及计算机系统
EP3718051A4 (fr) * 2017-12-03 2021-09-01 Mine One GmbH Recherche de correspondance stéréo

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US5608862A (en) * 1992-01-06 1997-03-04 Canon Kabushiki Kaisha Apparatus for processing hierarchically-coded image data

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Also Published As

Publication number Publication date
JP2002539533A (ja) 2002-11-19
AU2330600A (en) 2000-09-28
WO2000054181A1 (fr) 2000-09-14
CN1293783A (zh) 2001-05-02
KR20000054862A (ko) 2000-09-05
KR100319151B1 (ko) 2002-01-05
EP1080425A4 (fr) 2002-05-29
CN1165859C (zh) 2004-09-08
JP3541011B2 (ja) 2004-07-07

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