MX2016000994A - Identificacion de punto clave. - Google Patents
Identificacion de punto clave.Info
- Publication number
- MX2016000994A MX2016000994A MX2016000994A MX2016000994A MX2016000994A MX 2016000994 A MX2016000994 A MX 2016000994A MX 2016000994 A MX2016000994 A MX 2016000994A MX 2016000994 A MX2016000994 A MX 2016000994A MX 2016000994 A MX2016000994 A MX 2016000994A
- Authority
- MX
- Mexico
- Prior art keywords
- pixel
- image
- filtering
- value
- filtered
- Prior art date
Links
- 238000001914 filtration Methods 0.000 abstract 10
- 238000000034 method Methods 0.000 abstract 4
Classifications
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- 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
-
- 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
- G06V10/462—Salient features, e.g. scale invariant feature transforms [SIFT]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/10—Image enhancement or restoration using non-spatial domain filtering
-
- 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
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
- G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
-
- 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
- G06V10/56—Extraction of image or video features relating to colour
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Multimedia (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Image Analysis (AREA)
- Image Processing (AREA)
- Dc Digital Transmission (AREA)
Abstract
Se propone un método para identificar puntos clave en una imagen digital comprendiendo un conjunto de pixeles. Cada pixel tiene asociado al mismo un valor respectivo de un parámetro representativo de imagen. Dicho método comprende aproximar una imagen filtrada. Dicha imagen filtrada depende del parámetro de filtración y comprende para cada pixel de la imagen una función de filtrado que depende del parámetro de filtración para calcular un valor filtrado del valor de dicho parámetro representativo del pixel. Dicha aproximación comprende: a) generar un conjunto de imágenes filtradas de base; cada imagen filtrada de base es la imagen filtrada con el valor respectivo del parámetro de filtración; b) para cada pixel de por lo menos un sub-conjunto de dicho conjunto de pixeles, aproximar la función de filtración por medio de una función de aproximación respectiva con base en las imágenes filtradas de base; dicha función de aproximación es una función del parámetro de filtración dentro de un rango predefinido del parámetro de filtración; el método además comprende para cada pixel de dicho sub-conjunto, identificar tal pixel como un candidato punto clave si la función de aproximación tiene un extremo local el cual es también un extremo global con respecto al parámetro de filtración en un sub-conjunto respectivo interno a dicho rango predefinido. Para cada pixel identificado como candidato punto clave, el método además comprende: c) comparar el valor asumido por la función de aproximación en el valor del parámetro de filtración que corresponde al extremo global del pixel con los valores asumidos por las funciones de aproximación en los pixeles adyacentes en la imagen a los valores de los parámetros de filtración de los extremos globales respectivos de tales pixeles adyacentes, y d) seleccionar tal pixel con base en esta comparación.
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
IT001244A ITMI20131244A1 (it) | 2013-07-24 | 2013-07-24 | Identificazione di keypoint |
PCT/EP2014/065808 WO2015011185A1 (en) | 2013-07-24 | 2014-07-23 | Keypoint identification |
Publications (2)
Publication Number | Publication Date |
---|---|
MX2016000994A true MX2016000994A (es) | 2016-04-19 |
MX350657B MX350657B (es) | 2017-09-12 |
Family
ID=49118659
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
MX2016000994A MX350657B (es) | 2013-07-24 | 2014-07-23 | Identificación de punto clave. |
Country Status (12)
Country | Link |
---|---|
US (1) | US10152646B2 (es) |
EP (1) | EP3025273B1 (es) |
JP (1) | JP6499647B2 (es) |
KR (1) | KR102195826B1 (es) |
CN (1) | CN105493105B (es) |
BR (1) | BR112016001377B1 (es) |
CA (1) | CA2918947C (es) |
ES (1) | ES2939244T3 (es) |
IT (1) | ITMI20131244A1 (es) |
MX (1) | MX350657B (es) |
RU (1) | RU2663356C2 (es) |
WO (1) | WO2015011185A1 (es) |
Families Citing this family (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9576218B2 (en) * | 2014-11-04 | 2017-02-21 | Canon Kabushiki Kaisha | Selecting features from image data |
US10762349B2 (en) | 2015-12-30 | 2020-09-01 | Telecom Italia S.P.A. | System for generating 3D images for image recognition based positioning |
EP3239896B1 (en) | 2016-04-28 | 2018-11-28 | Joanneum Research Forschungsgesellschaft mbH | Data structure for describing an image sequence, and methods for extracting and matching these data structures |
CN106056636B (zh) * | 2016-05-31 | 2019-04-02 | 公安部禁毒情报技术中心 | 一种***片剂的标识特征信息提取方法 |
CN108648206B (zh) * | 2018-04-28 | 2022-09-16 | 成都信息工程大学 | 一种Robert边缘检测膜计算***及方法 |
CN111080674B (zh) * | 2019-12-18 | 2023-11-14 | 上海无线电设备研究所 | 一种基于混合高斯模型的多目标isar关键点提取方法 |
CN113627528A (zh) * | 2021-08-11 | 2021-11-09 | 江南大学 | 一种基于人眼视觉深度学习的国画所属画家自动识别方法 |
Family Cites Families (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6711293B1 (en) | 1999-03-08 | 2004-03-23 | The University Of British Columbia | Method and apparatus for identifying scale invariant features in an image and use of same for locating an object in an image |
US20050289519A1 (en) * | 2004-06-24 | 2005-12-29 | Apple Computer, Inc. | Fast approximation functions for image processing filters |
JP4605445B2 (ja) * | 2004-08-24 | 2011-01-05 | ソニー株式会社 | 画像処理装置および方法、記録媒体、並びにプログラム |
US7751639B1 (en) * | 2005-04-20 | 2010-07-06 | University Of East Anglia | Obtaining intrinsic images |
CN102763123B (zh) * | 2009-12-02 | 2015-03-25 | 高通股份有限公司 | 通过使查询图像和模型图像中的检测到的关键点成群集而进行特征匹配 |
US8582889B2 (en) * | 2010-01-08 | 2013-11-12 | Qualcomm Incorporated | Scale space normalization technique for improved feature detection in uniform and non-uniform illumination changes |
US9530073B2 (en) * | 2010-04-20 | 2016-12-27 | Qualcomm Incorporated | Efficient descriptor extraction over multiple levels of an image scale space |
RU2438174C1 (ru) * | 2010-06-15 | 2011-12-27 | Общество с ограниченной ответственностью "Томсклаб" | Способ распознавания объектов |
US9141871B2 (en) * | 2011-10-05 | 2015-09-22 | Carnegie Mellon University | Systems, methods, and software implementing affine-invariant feature detection implementing iterative searching of an affine space |
-
2013
- 2013-07-24 IT IT001244A patent/ITMI20131244A1/it unknown
-
2014
- 2014-07-23 ES ES14752573T patent/ES2939244T3/es active Active
- 2014-07-23 MX MX2016000994A patent/MX350657B/es active IP Right Grant
- 2014-07-23 JP JP2016528521A patent/JP6499647B2/ja active Active
- 2014-07-23 RU RU2016103624A patent/RU2663356C2/ru active
- 2014-07-23 WO PCT/EP2014/065808 patent/WO2015011185A1/en active Application Filing
- 2014-07-23 CN CN201480041493.1A patent/CN105493105B/zh active Active
- 2014-07-23 CA CA2918947A patent/CA2918947C/en active Active
- 2014-07-23 KR KR1020167002626A patent/KR102195826B1/ko active IP Right Grant
- 2014-07-23 US US14/906,218 patent/US10152646B2/en active Active
- 2014-07-23 BR BR112016001377-8A patent/BR112016001377B1/pt active IP Right Grant
- 2014-07-23 EP EP14752573.7A patent/EP3025273B1/en active Active
Also Published As
Publication number | Publication date |
---|---|
EP3025273A1 (en) | 2016-06-01 |
RU2016103624A3 (es) | 2018-05-21 |
CN105493105A (zh) | 2016-04-13 |
RU2016103624A (ru) | 2017-08-29 |
CA2918947C (en) | 2022-07-12 |
CN105493105B (zh) | 2018-12-28 |
BR112016001377B1 (pt) | 2023-01-24 |
KR20160034928A (ko) | 2016-03-30 |
CA2918947A1 (en) | 2015-01-29 |
MX350657B (es) | 2017-09-12 |
ES2939244T3 (es) | 2023-04-20 |
US10152646B2 (en) | 2018-12-11 |
WO2015011185A1 (en) | 2015-01-29 |
EP3025273B1 (en) | 2022-11-30 |
US20160155014A1 (en) | 2016-06-02 |
BR112016001377A2 (es) | 2017-08-29 |
RU2663356C2 (ru) | 2018-08-03 |
ITMI20131244A1 (it) | 2015-01-25 |
KR102195826B1 (ko) | 2020-12-29 |
JP6499647B2 (ja) | 2019-04-10 |
JP2016527634A (ja) | 2016-09-08 |
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