CN112085815B - Transformation method of polar coordinate image - Google Patents
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- 238000013507 mapping Methods 0.000 claims description 9
- 230000008602 contraction Effects 0.000 claims description 4
- 230000008961 swelling Effects 0.000 claims description 3
- 230000001131 transforming effect Effects 0.000 claims 4
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
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- G06T11/206—Drawing of charts or graphs
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/40—Filling a planar surface by adding surface attributes, e.g. colour or texture
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
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Abstract
The invention discloses a transformation method of a polar coordinate image, which comprises a polar coordinate system and a rectangular image, wherein the polar coordinate system takes a point o as a pole, takes ob as a polar diameter, and takes an ob angle as 0; the rectangular image is positioned at any position of the polar coordinates, and a geometric drawing board is utilized to draw a circumcircle of the rectangular image; the minimum polar diameter R and the minimum angle a of the circumscribed circle can be calculated by knowing the position of the center point c of the circumscribed circle and the circle radius R; selecting a two-dimensional matrix as a storage mode of a rectangular image in polar coordinates, wherein the origin of the two-dimensional matrix is the upper left corner; the horizontal direction is an angle component, and the initial angle is a; the vertical direction is a radial component, and the initial radius is r; the width and the height of the two-dimensional matrix are calculated by the radius R of the circumscribed circle through a transformation algorithm. The invention realizes the positioning and storage of rectangular images under a polar coordinate system, and effectively improves the expression and processing of polar coordinate images in the image processing process.
Description
Technical Field
The invention belongs to the technical field of image processing, and particularly relates to a transformation method of polar coordinate images.
Background
Digital images were first shown in the 50 s of the 20 th century, and electronic computers at that time have evolved to a level where people began to use computers to process graphic and image information; through the development of more than half a century, the subject of digital image processing is gradually perfected, a plurality of mature algorithms are produced, and the digital image processing method is widely applied to a plurality of fields of national economy.
However, the conventional digital images are all products under a rectangular coordinate system, and along with the increasing number of polar coordinate devices, an expression method of the digital images under the polar coordinate system and a corresponding processing algorithm are urgently needed.
Disclosure of Invention
The invention aims to provide a transformation method of polar coordinate images, which aims to solve the problems in the background technology. In order to achieve the purpose, the invention adopts the following technical scheme:
the expression method of the polar coordinate image comprises a polar coordinate system and a rectangular image, wherein the polar coordinate system takes a point o as a pole, takes ob as a polar diameter, and takes an ob angle as 0; the rectangular image is positioned at any position of the polar coordinates, and a geometric drawing board is utilized to draw a circumcircle of the rectangular image; calculating the minimum polar diameter R and the minimum angle a of the externally connected circle at the known position of the center point c of the externally connected circle and the circle radius R; selecting a two-dimensional matrix as a storage mode of the rectangular image in polar coordinates, wherein the origin of the two-dimensional matrix is the upper left corner; the horizontal direction is an angle component, and the initial angle is a; the vertical direction is a radial component, and the initial radius is r; the width and height of the two-dimensional matrix are calculated by the radius R of the circumscribed circle through an algorithm.
Further, the algorithm is a translation transformation algorithm, and when a circle is translated from a point s to a point c, h is a translation distance, and m is a translation angle; the specific translation transformation algorithm comprises the following steps:
Step 1, calculating parameters of a target image to obtain a two-dimensional matrix of the target image; knowing the coordinates (oc, n) of the point c of the center of the target image and the radius R of the circle, calculating an angle e=arcsin (R/oc); then the starting angle a=n-e of the rectangular image in the two-dimensional matrix is obtained, and the starting radius r=oc-R is obtained, wherein the width of the two-dimensional matrix is 2e, and the height is 2R;
Step 2, mapping each point of the target image to the original image to obtain a corresponding color value; knowing the point (r 1,a1) of the target graph, assuming that the point mapped to the original graph is (r 0,a0), calculating the coordinate value of the point (r 0,a0) of the original graph according to the formulas r 0cos a0＝r1cos a1 -h cos m and r 0sin a0＝r1sin a1 -h sin m, and then selecting an interpolation mode to obtain the color value.
Further, the algorithm is a rotation transformation algorithm, a circle rotates around a circle center c by an arbitrary angle θ, and the specific rotation transformation algorithm includes the following steps:
step 1, calculating parameters of a target image to obtain a two-dimensional matrix of the rectangular image: because the circumscribing circle rotates around the circle center, the size and the position of the circumscribing circle are unchanged, and the initial angle, the initial radius, the width and the height of the target graph matrix are the same as those of the original graph;
Step 2, mapping each point of the target image to the original image to obtain a corresponding color value; knowing the point (r 1,a1) of the target graph, assuming that the point mapped to the original graph is (r 0,a0), the coordinate values of the point (r 0,a0) of the original graph are calculated according to formulas r0cos a0＝(r1cos a1-oc cos n)cosθ+(r1sin a1-oc sin n)sinθ+oc cos n and r0sin a0＝(r1sin a1-oc sin n)cosθ-(r1cos a1-oc cos n)sinθ+oc sin n, and then an interpolation mode is selected to obtain the color value.
Further, the algorithm is a collapsible transformation algorithm, the center position of a circle is unchanged, but the radius is changed, and the collapsible coefficient of the radius is assumed to be beta; the specific expansion and contraction transformation algorithm comprises the following steps:
Step1, calculating parameters of a target image to obtain a two-dimensional matrix of the target image; knowing the coordinates (oc, n) of the center c point of the target image and the radius R of the circle, the angle e=arcsin (R/oc) is calculated, and then the starting angle a=n-e of the target image matrix is obtained, the starting radius r=oc-R, and the width of the two-dimensional matrix is 2e and the height is 2R.
Step 2, mapping each point of the target image to the original image to obtain a corresponding color value; knowing the point (r 1,a1) of the target graph, assuming that the point mapped to the original graph is (r 0,a0), calculating the coordinate value of the point (r 0,a0) of the original graph according to formulas r 0sin a0＝oc sin n(1-1/β)+r1sin a1/beta and r 0cos a0＝oc cos n(1-1/β)+r1cos a1/beta, and then selecting an interpolation mode to obtain the color value.
Further, the interpolation mode is nearest neighbor interpolation, bilinear interpolation or cubic interpolation.
The invention has the beneficial effects that:
the invention realizes the positioning and storage of rectangular images under a polar coordinate system, and effectively improves the expression and processing algorithm of the polar coordinate images in the image processing process.
Drawings
Fig. 1 is: schematic diagram of parameter calculation method of image under polar coordinates;
Fig. 2 is: a storage mode schematic diagram of the polar coordinate image;
Fig. 3 is: a translation transformation algorithm schematic diagram of the polar coordinate image;
Fig. 4 is: a rotation transformation algorithm schematic diagram of the polar coordinate image;
fig. 5 is: a schematic diagram of a swelling and shrinking transformation algorithm of the polar coordinate image.
Detailed Description
In order that the invention may be readily understood, a more complete description of the invention will be rendered by reference to the appended drawings. The drawings illustrate preferred embodiments of the invention. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
It will be understood that when an element is referred to as being "fixed to" another element, it can be directly on the other element or intervening elements may also be present. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present. In contrast, when an element is referred to as being "directly on" another element, there are no intervening elements present. The terms "vertical," "horizontal," "left," "right," and the like are used herein for illustrative purposes only and are not meant to be the only embodiments, and the terms "upper," "lower," "left," "right," "front," "back," and the like are used herein with reference to the positional relationship of the drawings.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
The technical scheme of the patent is further described in detail below with reference to the specific embodiments.
Embodiment one:
1-2, an expression method of a polar coordinate image comprises a polar coordinate system and a rectangular image, wherein the polar coordinate system takes a point o as a pole, takes ob as a polar diameter, and takes an ob angle as 0; the rectangular image is positioned at any position of the polar coordinates, and a geometric drawing board is utilized to draw a circumcircle of the rectangular image; calculating the minimum polar diameter R and the minimum angle a of the externally connected circle at the known position of the center point c of the externally connected circle and the circle radius R; selecting a two-dimensional matrix as a storage mode of a rectangular image in polar coordinates, wherein the origin of the two-dimensional matrix is the upper left corner; the horizontal direction is an angle component, and the initial angle is a; the vertical direction is a radial component, and the initial radius is r; the width and height of the two-dimensional matrix are calculated by the radius R of the circumscribed circle through an algorithm.
A transformation method of a polar coordinate image comprises a transformation algorithm for calculating the width and the height of a two-dimensional matrix by utilizing the radius R of an circumcircle, and an algorithm corresponding to the polar coordinate image is obtained according to an expression method of the polar coordinate image and calculation formulas of translation, rotation and expansion and contraction.
In this embodiment, as shown in fig. 3, the corresponding algorithm is a translation transformation algorithm, and when a circle translates from a point s to a point c, h is a translation distance, and m is a translation angle; the specific translation transformation algorithm comprises the following steps:
Step 1, calculating parameters of a target image to obtain a two-dimensional matrix of the target image; knowing the coordinates (oc, n) of the point c of the center of the target image and the radius R of the circle, calculating an angle e=arcsin (R/oc); then the initial angle a=n-e of the rectangular image in the two-dimensional matrix and the initial radius r=oc-R are obtained, and the width of the two-dimensional matrix is 2e and the height is 2R;
Step 2, mapping each point of the target image to the original image to obtain a corresponding color value; knowing the point (r 1,a1) of the target graph, assuming that the point mapped to the original graph is (r 0,a0), calculating the coordinate value of the point (r 0,a0) of the original graph according to the formulas r 0cos a0＝r1cos a1 -h cos m and r 0sin a0＝r1sin a1 -h sin m, and then selecting an interpolation mode to obtain the color value.
Embodiment two:
the present embodiment is a supplement to the first embodiment, as shown in fig. 4, and according to the transformation situation, the corresponding algorithm is a rotation transformation algorithm, that is, when a circumscribed circle rotates around the center c by an arbitrary angle θ, the specific rotation transformation algorithm includes the following steps:
step 1, calculating parameters of a target image to obtain a two-dimensional matrix of a rectangular image: because the circumscribing circle rotates around the circle center, the size and the position of the circumscribing circle are unchanged, and the initial angle, the initial radius, the width and the height of the target graph matrix are the same as those of the original graph;
Step 2, mapping each point of the target image to the original image to obtain a corresponding color value; knowing the point (r 1,a1) of the target graph, assuming that the point mapped to the original graph is (r 0,a0), the coordinate values of the point (r 0,a0) of the original graph are calculated according to formulas r0cos a0＝(r1cos a1-oc cos n)cosθ+(r1sin a1-oc sin n)sinθ+oc cos n and r0sin a0＝(r1sin a1-oc sin n)cosθ-(r1cos a1-oc cos n)sinθ+oc sin n, and then an interpolation mode is selected to obtain the color value.
Embodiment III:
The specific embodiment is based on the embodiment, as shown in fig. 5, according to the transformation condition, the corresponding algorithm is a collapsible transformation algorithm, that is, when the center position of a circle is unchanged, but the radius is changed, and the collapsible coefficient of the radius is assumed to be beta; the specific expansion and contraction transformation algorithm comprises the following steps:
Step1, calculating parameters of a target image to obtain a two-dimensional matrix of the target image; knowing the coordinates (oc, n) of the center c point of the target image and the radius R of the circle, calculating an angle e=arcsin (R/oc), and obtaining a starting angle a=n-e of the target image matrix, wherein the starting radius r=oc-R, the width of the two-dimensional matrix is 2e, and the height is 2R;
Step 2, mapping each point of the target image to the original image to obtain a corresponding color value; knowing the point (r 1,a1) of the target graph, assuming that the point mapped to the original graph is (r 0,a0), calculating the coordinate value of the point (r 0,a0) of the original graph according to formulas r 0sin a0＝oc sin n(1-1/β)+r1sin a1/beta and r 0cos a0＝oc cos n(1-1/β)+r1cos a1/beta, and then selecting an interpolation mode to obtain the color value.
In this embodiment, the interpolation mode may select one of nearest neighbor interpolation, bilinear interpolation, or cubic interpolation to perform interpolation calculation, so as to obtain different RGB color values.
The above embodiments are only for illustrating the present invention, not for limiting the present invention, and various changes and modifications may be made by one skilled in the relevant art without departing from the spirit and scope of the present invention, so that all equivalent technical solutions are also within the scope of the present invention, and the scope of the present invention is defined by the claims.
Claims (5)
1. A transformation method of polar coordinate image is characterized in that: the method comprises a polar coordinate system and a rectangular image, wherein the polar coordinate system takes a point o as a pole, takes ob as a polar diameter, and takes an ob angle as 0; the rectangular image is positioned at any position of the polar coordinates, and a geometric drawing board is utilized to draw a circumcircle of the rectangular image; calculating the minimum polar diameter R and the minimum angle a of the externally connected circle at the known position of the center point c of the externally connected circle and the circle radius R; selecting a two-dimensional matrix as a storage mode of the rectangular image in polar coordinates, wherein the origin of the two-dimensional matrix is the upper left corner; the horizontal direction is an angle component, and the initial angle is a; the vertical direction is a radial component, and the initial radius is r; the width and the height of the two-dimensional matrix are calculated by the radius R of the circumscribing circle.
2. A method of transforming polar images according to claim 1, characterized in that: the method is a translation transformation method, when a circle is translated from a point s to a point c, h is a translation distance, and m is a translation angle; the specific translation transformation method comprises the following steps:
Step 1, calculating parameters of a target image to obtain a two-dimensional matrix of the target image; knowing the coordinates (oc, n) of the point c of the center of the target image and the radius R of the circle, calculating an angle e=arcsin (R/oc); then the starting angle a=n-e of the rectangular image in the two-dimensional matrix is obtained, and the starting radius r=oc-R is obtained, wherein the width of the two-dimensional matrix is 2e, and the height is 2R;
step 2, mapping each point of the target image to the original image to obtain a corresponding color value; knowing the point (r 1,a1) of the target graph, assuming that the point mapped to the original graph is (r 0,a0), calculating the coordinate value of the point (r 0,a0) of the original graph according to formulas r 0cosa0＝r1cosa1 -hcosm and r 0sina0＝r1sina1 -hsinm, and then selecting an interpolation mode to obtain the color value.
3. A method of transforming polar images according to claim 1, characterized in that: the method is a rotation transformation method, a circle rotates around a circle center c by any angle theta, and the specific rotation transformation method comprises the following steps:
step 1, calculating parameters of a target image to obtain a two-dimensional matrix of the rectangular image: because the circumscribing circle rotates around the circle center, the size and the position of the circumscribing circle are unchanged, and the initial angle, the initial radius, the width and the height of the target graph matrix are the same as those of the original graph;
Step 2, mapping each point of the target image to the original image to obtain a corresponding color value; knowing the point (r 1,a1) of the target graph, assuming that the point mapped to the original graph is (r 0,a0), the coordinate values of the point (r 0,a0) of the original graph are calculated according to formulas r0cosa0＝(r1cosa1-occosn)cosθ+(r1sina1-ocsinn)sinθ+occosn and r0sina0＝(r1sina1-ocsinn)cosθ-(r1cosa1-occosn)sinθ+ocsinn, and then an interpolation mode is selected to obtain the color value.
4. A method of transforming polar images according to claim 1, characterized in that: the method is a swelling and shrinking transformation method, the circle center position of a circle is unchanged, but the radius is changed, and the swelling and shrinking coefficient of the radius is assumed to be beta; the specific expansion and contraction transformation method comprises the following steps:
Step1, calculating parameters of a target image to obtain a two-dimensional matrix of the target image; knowing the coordinates (oc, n) of the center c point of the target image and the radius R of the circle, calculating an angle e=arcsin (R/oc), and obtaining a starting angle a=n-e of the target image matrix, wherein the starting radius r=oc-R, the width of the two-dimensional matrix is 2e, and the height is 2R;
Step 2, mapping each point of the target image to the original image to obtain a corresponding color value; knowing the point (r 1,a1) of the target graph, assuming that the point mapped to the original graph is (r 0,a0), calculating the coordinate value of the point (r 0,a0) of the original graph according to formulas r 0sina0＝ocsinn(1-1/β)+r1sina1/beta and r 0cosa0＝occosn(1-1/β)+r1cosa1/beta, and then selecting an interpolation mode to obtain the color value.
5. A method of transforming polar images according to any of claims 2-4, wherein: the interpolation mode is nearest neighbor interpolation, bilinear interpolation or cubic interpolation.
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006309802A (en) * | 2006-08-17 | 2006-11-09 | Sony Corp | Image processor and image processing method |
| US7751621B1 (en) * | 2007-01-30 | 2010-07-06 | Jacobsen Kenneth P | Method and system for rapid object recall within images |
| CN102750669A (en) * | 2012-05-29 | 2012-10-24 | 山东神思电子技术股份有限公司 | Image rotation processing method |
| WO2015191283A1 (en) * | 2014-06-09 | 2015-12-17 | Petrocy Richard | Modularized display apparatus, self-addressing apparatus and associated methods |
| CN105509729A (en) * | 2015-11-16 | 2016-04-20 | 中国航天时代电子公司 | Bionic-tentacle-based robot autonomous navigation method |
| CN106651775A (en) * | 2016-12-16 | 2017-05-10 | 西安汇明光电技术有限公司 | Optimization method for log-polar coordinate transformation based on digital image processing |
| CN108257136A (en) * | 2018-02-09 | 2018-07-06 | 天津海达奥普光电技术股份有限公司 | A kind of image partition method of corn seed Shape Feature Extraction |
| CN110059719A (en) * | 2019-03-18 | 2019-07-26 | 西北工业大学 | A kind of target identification method of the image moment based on Walsh transformation |
| CN110232438A (en) * | 2019-06-06 | 2019-09-13 | 北京致远慧图科技有限公司 | The image processing method and device of convolutional neural networks under a kind of polar coordinate system |
| CN110415177A (en) * | 2019-07-26 | 2019-11-05 | 四川长虹电器股份有限公司 | A kind of image rotation sanction drawing method based on Java |
| CN110815202A (en) * | 2018-08-07 | 2020-02-21 | 杭州海康机器人技术有限公司 | Obstacle detection method and device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100988872B1 (en) * | 2009-07-08 | 2010-10-20 | 주식회사 나노포토닉스 | Method and imaging system for obtaining complex images using rotationally symmetric wide-angle lens and image sensor for hardwired image processing |
-
2020
- 2020-09-14 CN CN202010962408.2A patent/CN112085815B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006309802A (en) * | 2006-08-17 | 2006-11-09 | Sony Corp | Image processor and image processing method |
| US7751621B1 (en) * | 2007-01-30 | 2010-07-06 | Jacobsen Kenneth P | Method and system for rapid object recall within images |
| CN102750669A (en) * | 2012-05-29 | 2012-10-24 | 山东神思电子技术股份有限公司 | Image rotation processing method |
| WO2015191283A1 (en) * | 2014-06-09 | 2015-12-17 | Petrocy Richard | Modularized display apparatus, self-addressing apparatus and associated methods |
| CN105509729A (en) * | 2015-11-16 | 2016-04-20 | 中国航天时代电子公司 | Bionic-tentacle-based robot autonomous navigation method |
| CN106651775A (en) * | 2016-12-16 | 2017-05-10 | 西安汇明光电技术有限公司 | Optimization method for log-polar coordinate transformation based on digital image processing |
| CN108257136A (en) * | 2018-02-09 | 2018-07-06 | 天津海达奥普光电技术股份有限公司 | A kind of image partition method of corn seed Shape Feature Extraction |
| CN110815202A (en) * | 2018-08-07 | 2020-02-21 | 杭州海康机器人技术有限公司 | Obstacle detection method and device |
| CN110059719A (en) * | 2019-03-18 | 2019-07-26 | 西北工业大学 | A kind of target identification method of the image moment based on Walsh transformation |
| CN110232438A (en) * | 2019-06-06 | 2019-09-13 | 北京致远慧图科技有限公司 | The image processing method and device of convolutional neural networks under a kind of polar coordinate system |
| CN110415177A (en) * | 2019-07-26 | 2019-11-05 | 四川长虹电器股份有限公司 | A kind of image rotation sanction drawing method based on Java |
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