CN107490342A - A kind of cell phone appearance detection method based on single binocular vision - Google Patents

A kind of cell phone appearance detection method based on single binocular vision Download PDF

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Publication number
CN107490342A
CN107490342A CN201710520300.6A CN201710520300A CN107490342A CN 107490342 A CN107490342 A CN 107490342A CN 201710520300 A CN201710520300 A CN 201710520300A CN 107490342 A CN107490342 A CN 107490342A
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CN
China
Prior art keywords
camera
mobile phone
binocular
cell phone
binocular vision
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CN201710520300.6A
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Chinese (zh)
Inventor
张美杰
张平
张乐宇
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广东工业大学
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Priority to CN201710520300.6A priority Critical patent/CN107490342A/en
Publication of CN107490342A publication Critical patent/CN107490342A/en

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Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00Measuring arrangements characterised by the use of optical means
    • G01B11/02Measuring arrangements characterised by the use of optical means for measuring length, width or thickness
    • G01B11/022Measuring arrangements characterised by the use of optical means for measuring length, width or thickness by means of tv-camera scanning
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00Measuring arrangements characterised by the use of optical means
    • G01B11/02Measuring arrangements characterised by the use of optical means for measuring length, width or thickness
    • G01B11/06Measuring arrangements characterised by the use of optical means for measuring length, width or thickness for measuring thickness, e.g. of sheet material
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00Measuring arrangements characterised by the use of optical means
    • G01B11/08Measuring arrangements characterised by the use of optical means for measuring diameters
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00Measuring arrangements characterised by the use of optical means
    • G01B11/24Measuring arrangements characterised by the use of optical means for measuring contours or curvatures

Abstract

The present invention relates to a kind of cell phone appearance detection method based on single binocular vision, pass through Binocular vision photogrammetry mobile phone thickness, mobile phone length and width dimensions and fillet information are measured by monocular vision, the cell phone appearance data detected are compared with standard value, calculating difference simultaneously generates form, product of failing will be considered as beyond the mobile phone of allowable error scope according to form, be sorted to by manipulator and reprocess area.The present invention has the advantages that testing result accurate rate is high, detection efficiency is high, testing cost is low, non-contact.

Description

A kind of cell phone appearance detection method based on single binocular vision

Technical field

The present invention relates to the technical field of mobile phone detection, more particularly to a kind of cell phone appearance inspection based on single binocular vision Survey method.

Background technology

Nowadays electronic product has been enter into the various aspects of people's life, people are not enjoying electronic product institute band all the time That comes is convenient and swift.By taking mobile phone as an example, in the world, human hand one is substantially reached.Such huge market demand Also more stern challenge is proposed to handset manufacturers.The quality testing of mobile phone turns into the deciding factor for seizing the market share. Among these, the outward appearance detection of mobile phone is a ring critically important in the whole quality testing of mobile phone.Traditional cell phone appearance detects Contact type measurement, i.e. manipulator capture mobile phone, are placed into Standard Module, see whether it matches with mould.This detection Be present many deficiencies in mode, for example take time and effort, and cost is high, and manipulator crawl causes the infringement to mobile phone.So propose A kind of new non-contact detection is necessary.

The content of the invention

It is an object of the invention to overcome the deficiencies of the prior art and provide a kind of testing result accurate rate height, detection efficiency It is high, testing cost is low, the contactless cell phone appearance detection method based on single binocular vision.

To achieve the above object, technical scheme provided by the present invention is:Standard value and allowable error scope are obtained, is passed through Binocular vision photogrammetry mobile phone thickness, by monocular vision measurement mobile phone length and width dimensions and fillet information, outside the mobile phone detected Data are seen compared with standard value, calculating difference simultaneously generates form, will be regarded according to form beyond the mobile phone of allowable error scope For product of failing, it is sorted to by manipulator and reprocesses area.

The standard value and allowable error scope of the above-mentioned handset size used obtain at manufacturer, specifically include:Hand Machine length and width size, thickness, radius of corner, the standard value and allowable error scope of arc length and circular arc degree.

Further, Binocular vision photogrammetry mobile phone thickness, specifically includes following steps:

1) binocular camera is demarcated, and obtains the inside and outside parameter and distortion factor of left and right camera;

2) camera is corrected, and removes the influence of optical distortion, binocular camera is changed into canonical form;

3) binocular ranging, the match point between camera is calculated, obtains disparity map;

4) according to disparity map, mobile phone thickness is calculated;

5) Pixel Dimensions of mobile phone thickness are converted into actual size.

Further, what binocular camera was demarcated comprises the following steps that:

1-1) left camera camera calibration, obtain camera inside and outside parameter;

1-2) right camera camera calibration, obtain camera inside and outside parameter;

1-3) binocular calibration, obtain the translation rotation relationship between camera.

Further, binocular ranging comprises the following steps that:

3-1) matching error calculates;

3-2) matching error integrates;

3-3) calculate disparity map;

3-4) disparity map is handled.

Further, it is specific that parallax is carried out using the global Stereo Matching Algorithm that algorithm is cut based on figure when calculating disparity map The calculating of figure.

Further, disparity map is handled, and is specially:The salt-pepper noise of disparity map is removed using medium filtering and it fails to match Isolated point.

Further, monocular vision measurement mobile phone length and width dimensions and fillet information, it uses the right shooting of above-mentioned demarcation Head collection image, is concretely comprised the following steps:

(1 edge pixel detects, and obtains mobile phone outer contour;

(outer contour is converted into minimum enclosed rectangle by 2, calculates rectangular aspect size;

(3 segmentation mobile phone radius areas, calculate its characteristic parameter, including arc length, circular arc degree and radius;

(obtained Pixel Dimensions are converted into actual size by 4.

This programme principle and advantage are as follows:

This programme measures mobile phone length and width dimensions by monocular vision and fillet is believed by Binocular vision photogrammetry mobile phone thickness Breath, for the cell phone appearance data detected compared with standard value, calculating difference simultaneously generates form, and will be exceeded according to form allows The mobile phone of error range is considered as product of failing, and is sorted to by manipulator and reprocesses area.

This programme has the advantages that testing result accurate rate is high, detection efficiency is high, testing cost is low, non-contact.

Brief description of the drawings

Fig. 1 is a kind of flow chart of the cell phone appearance detection method based on single binocular vision of the present invention;

Fig. 2 is Binocular vision photogrammetry mobile phone thickness in a kind of cell phone appearance detection method based on single binocular vision of the present invention Flow chart;

Fig. 3 measures mobile phone length and width for monocular vision in a kind of cell phone appearance detection method based on single binocular vision of the present invention The flow chart of size and fillet information.

Embodiment

With reference to specific embodiment, the invention will be further described:

Referring to shown in accompanying drawing 1-3, a kind of cell phone appearance detection method based on single binocular vision described in the present embodiment, wrap Include following steps:

S1, at manufacturer obtain handset size standard value and allowable error scope, specifically include:Mobile phone length and width Size, thickness, radius of corner, the standard value and allowable error scope of arc length and circular arc degree.

S2, Binocular vision photogrammetry mobile phone thickness, including:

S21, binocular camera demarcation, obtain the inside and outside parameter and distortion factor of left and right camera, are specially:

1) left camera camera calibration, obtains camera inside and outside parameter, and formula is:

Wherein, if left camera O-xlylzlAt the origin of world coordinate system and without spin, image coordinate system Ol- XlYl,(Xl,Yl) for left camera shooting image coordinate, flFor the effective focal length of left camera.

2) right camera camera calibration, obtains camera inside and outside parameter, and formula is:

Similarly, right camera O-xryrzrAt the origin of world coordinate system and without spin, image coordinate system Or-XrYr, (Xr,Yr) for right camera shooting image coordinate, frFor the effective focal length of right camera.

3) binocular calibration, obtains the translation rotation relationship between camera, and calculation formula is:

Wherein,Respectively O-xlylzlCoordinate system and O-xryrzrRotation between coordinate system Translation transformation vector between torque battle array and origin.

For O-xlylzlSpatial point in coordinate system, the corresponding relation between 2 camera image planes points are:

A point P on mobile phone1(X1,Y1,Z1) three-dimensional coordinate be:

Wherein,Pl、PrRespectively spatial point P is in the magazine image coordinate in left and right, Ml、MrIt is respectively left The projection matrix of right camera, XwFor spatial point world coordinate system three-dimensional coordinate;

Wherein,

Zc1、Zc2The respectively z-axis coordinate of the camera coordinates system of two cameras of left and right, (u1,v1, 1) and (u2,v2, 1) be respectively Pl、PrHomogeneous coordinates of the point in respective image, (X, Y, Z, 1) is homogeneous coordinates of the P points under world coordinate system; Represent the i-th row jth column element of projection matrix.

Similarly, characteristic point P corresponding with P on mobile phone is asked for2(X2,Y2,Z2) three-dimensional coordinate.

S22, camera correction, remove the influence of optical distortion, binocular camera are changed into canonical form.

S23, binocular ranging, the match point between camera is calculated, obtains disparity map;Including:

1) matching error calculates:

If the extraction accuracy of the two camera X-directions in left and right is respectively δ X1、δX2, the extraction accuracy of Y-direction is respectively δ Y1、δ Y2, then a point P is in the measurement accuracy of X-direction on mobile phone:

The measurement accuracy of P in the Y direction is:

P is in the measurement accuracy of Z-direction:

Then the overall measurement accuracy of P points is:

2) matching error integrates.

3) disparity map is calculated:

The calculating of disparity map is carried out using the global Stereo Matching Algorithm that algorithm is cut based on mean shift figures.It is if to be matched Target image I pixel size is M × N, and template T pixel size is m × n.One piece of pixel is arbitrarily chosen from target image I Size is m × n subgraph Ix,y, coordinate of its upper left corner in image I is (x, y), wherein, 0≤x≤M-m, 0≤y≤N-n, M, N are respectively the line number and columns of image pixel to be matched, and m, n are respectively the line number and columns of template pixel;R (x, y) is son Scheme Ix,yWith template T normalized crosscorrelation value, then:

In formula, (i, j) is the coordinate of pixel in a template,

For subgraph Ix,yPixel average;

For template T pixel average.

4) disparity map is handled:The salt-pepper noise of disparity map and the isolated point that it fails to match are removed using medium filtering.

S24, according to disparity map, calculate mobile phone thickness:

By above-mentioned P, P2 being calculated, the space length d of point-to-point transmission is calculated:

S25, the Pixel Dimensions of mobile phone thickness are converted into actual size:

D=kd

Wherein, D is actual size, and d is Pixel Dimensions, and k is corresponding linear coefficient.

S3, monocular vision measurement mobile phone length and width dimensions and fillet information, figure is gathered using the right camera of above-mentioned demarcation Picture, image processing flow are:

S31, edge pixel detection, obtain mobile phone outer contour:

1) edge pixel detects, and obtains mobile phone face profile;

2) the maximum contour line of length, as mobile phone outer contour are selected.

S32, outer contour is converted into minimum enclosed rectangle, calculates rectangular aspect size:

Take minimum enclosed rectangle to take the upper left corner and lower right corner characteristic point, be designated as respectively (Row1, Column1) and (Row2, Column2), two rows subtract each other to obtain that rectangle is wide, and two row subtract each other to obtain rectangle length, so as to obtain the pixel that medical bag decorates drop length and width Size.

S33, segmentation mobile phone radius area, calculate its characteristic parameter, including arc length, circular arc degree and radius:

1) outer contour is converted into minimal convex polygon, obtains center O point coordinates;

2) using convex polygon center O as end points, a horizontal straight line parallel to convex polygon upper bottom edge, direction water are generated Put down to the left, A points are met at convex polygon left side.Similarly, using center as end points, generation one is parallel to convex polygon upper bottom edge Horizontal straight line, direction level meets at B points to the right, with convex polygon right edge.Similarly, it is raw using convex polygon center as end points Into a longitudinal straight line parallel to convex polygon left side, direction is horizontal upwards, and C points are met at convex polygon upper bottom edge.Together Reason, using convex polygon center as end points, a longitudinal straight line parallel to convex polygon left side being generated, direction is horizontal downwards, D points are met at convex polygon bottom.

3) upper left side region is scanned.The horizontal straight line OA levels of generation are moved up, are scanned line by line.It is mobile every time One pixel, calculate line segment OA length.Similarly, longitudinal straight line OC of generation is moved to the left vertically, be scanned by column, often Secondary one pixel of movement, calculate line segment OC length.

4) when line segment OA length values jump (being obviously reduced) by stable generation, scanning is stopped.Record the point Pixel coordinate Ai(xi,ym) and Ci(xp,yj), the point is the two-end-point of mobile phone upper left corner fillet.

5) by fillet extreme coordinates, circular arc portion is split.Calculate its characteristic parameter, including arc length, circular arc degree and Radius.

6) upper right side, lower left, lower right region are scanned successively with same method.Its fillet extreme coordinates is determined, will Circular arc portion is split, and calculates its characteristic parameter;Wherein, rad=L/R, rad are radian, and L is arc length, and R is radius.

S34, obtained Pixel Dimensions are converted into actual size.

S4, by the actual size data that step S2 and S3 are measured with compared with standard value, calculating difference simultaneously generates report Table.

S5, product of failing will be considered as beyond the mobile phone of allowable error scope according to form, be sorted to and reprocessed by manipulator Area.

The present embodiment detection method has that testing result accurate rate is high, detection efficiency is high, testing cost is low, non-contact etc. excellent Point.

Examples of implementation described above are only the preferred embodiments of the invention, and the implementation model of the present invention is not limited with this Enclose, therefore the change that all shape, principles according to the present invention are made, it all should cover within the scope of the present invention.

Claims (7)

  1. A kind of 1. cell phone appearance detection method based on single binocular vision, it is characterised in that:It is thick by Binocular vision photogrammetry mobile phone Degree, mobile phone length and width dimensions and fillet information are measured by monocular vision, the cell phone appearance data detected are carried out with standard value Compare, calculating difference simultaneously generates form, will be considered as product of failing beyond the mobile phone of allowable error scope according to form, by machinery Hand, which is sorted to, reprocesses area.
  2. A kind of 2. cell phone appearance detection method based on single binocular vision according to claim 1, it is characterised in that:It is described Binocular vision photogrammetry mobile phone thickness, specifically includes following steps:
    1) binocular camera is demarcated, and obtains the inside and outside parameter and distortion factor of left and right camera;
    2) camera is corrected, and removes the influence of optical distortion, binocular camera is changed into canonical form;
    3) binocular ranging, the match point between camera is calculated, obtains disparity map;
    4) according to disparity map, mobile phone thickness is calculated;
    5) Pixel Dimensions of mobile phone thickness are converted into actual size.
  3. A kind of 3. cell phone appearance detection method based on single binocular vision according to claim 2, it is characterised in that:It is described The demarcation of step 1) binocular camera comprises the following steps that:
    1-1) left camera camera calibration, obtain camera inside and outside parameter;
    1-2) right camera camera calibration, obtain camera inside and outside parameter;
    1-3) binocular calibration, obtain the translation rotation relationship between camera.
  4. A kind of 4. cell phone appearance detection method based on single binocular vision according to claim 2, it is characterised in that:It is described Step 3) binocular ranging comprises the following steps that:
    3-1) matching error calculates;
    3-2) matching error integrates;
    3-3) calculate disparity map;
    3-4) disparity map is handled.
  5. A kind of 5. cell phone appearance detection method based on single binocular vision according to claim 4, it is characterised in that:It is described Step 3-3) disparity map is calculated, be specially:The calculating of disparity map is carried out using the global Stereo Matching Algorithm that algorithm is cut based on figure.
  6. A kind of 6. cell phone appearance detection method based on single binocular vision according to claim 4, it is characterised in that:It is described Step 3-4) disparity map processing, be specially:The salt-pepper noise of disparity map and the isolated point that it fails to match are removed using medium filtering.
  7. A kind of 7. cell phone appearance detection method based on single binocular vision according to claim 1, it is characterised in that:It is described Comprising the following steps that for mobile phone length and width dimensions and fillet information is measured by monocular vision:
    (1 edge pixel detects, and obtains mobile phone outer contour;
    (outer contour is converted into minimum enclosed rectangle by 2, calculates rectangular aspect size;
    (3 segmentation mobile phone radius areas, calculate its characteristic parameter, including arc length, circular arc degree and radius;
    (obtained Pixel Dimensions are converted into actual size by 4.
CN201710520300.6A 2017-06-30 2017-06-30 A kind of cell phone appearance detection method based on single binocular vision CN107490342A (en)

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Cited By (5)

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CN108458668A (en) * 2018-01-05 2018-08-28 燕山大学 Slab edge and Head and Tail Shape automatic checkout system based on binocular vision and method
CN109297402A (en) * 2018-08-21 2019-02-01 苏州图锐智能科技有限公司 Tin cream detection device based on technique of binocular stereoscopic vision
CN109878113A (en) * 2019-04-04 2019-06-14 成都联科航空技术有限公司 For cutting the detection method of the automatic blanking machine cutting accuracy of carbon fiber prepreg
CN110360934A (en) * 2019-07-15 2019-10-22 北海市龙浩光电科技有限公司 A method of measurement globoidal glass cover board
CN110470216A (en) * 2019-07-10 2019-11-19 湖南交工智能技术有限公司 A kind of three-lens high-precision vision measurement method and device

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CN102441581A (en) * 2010-09-30 2012-05-09 邓玥 Machine vision-based device and method for online detection of structural steel section size
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CN109297402A (en) * 2018-08-21 2019-02-01 苏州图锐智能科技有限公司 Tin cream detection device based on technique of binocular stereoscopic vision
CN109878113A (en) * 2019-04-04 2019-06-14 成都联科航空技术有限公司 For cutting the detection method of the automatic blanking machine cutting accuracy of carbon fiber prepreg
CN110470216A (en) * 2019-07-10 2019-11-19 湖南交工智能技术有限公司 A kind of three-lens high-precision vision measurement method and device
CN110360934A (en) * 2019-07-15 2019-10-22 北海市龙浩光电科技有限公司 A method of measurement globoidal glass cover board

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Application publication date: 20171219