Robust and Accurate Surface MeasurementUsing Structured LightIEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 57, NO. 6, JUNE 2008Rongqian Yang, Sheng Cheng, Wei Yang, and Yazhu ChenPPT 製作 100 %

Adviser : 謝銘原Student: 謝琮閔

ID : M9820113

Outline•Abstract•Introduction•System design•Structured light exaction and coding

procedure•Experimental results•Discussion and conclusion

Abstract•3-D surfaces using a binocular system•Each structured light sheet is fitted to a

conicoid•Zero-crossing detection algorithm with

Steger’s detector •Linked line with the gray code to avoid

producing outliers caused by erroneous decoding

INTRODUCTION•Structured light measurement methods

for 3-D coordinate acquisition have been rapidly developing and have been applied in various domains.

•The accuracy of measurement is related to the distortion of LCD projector lens and the subpixel location of stripes.

INTRODUCTION•Classic stereo vision system•Steger’s curvilinear structure detection

method•Gray code•Dynamic threshold•Per-pixel varying threshold and

oversampling

INTRODUCTION•Each structured light sheet is regarded as

a conicoid

•Ridgeline linking algorithm is also employed to link the subpixel points in a stripe and construct a data list

•Gray code separates the measurement area into a great number of divisions

SYSTEM DESIGN•System employs two digital cameras to

reduce the shading area on the object surface

•The system model, as shown in Fig. 1, consists mainly of two charge-coupled device (CCD) cameras and one LCD projector.

SYSTEM DESIGN

SYSTEM DESIGN•In Fig. 1,

indicate the left, right, and global coordinate systems

•These coordinate systems can be related to each other using the following formulas:

SYSTEM DESIGN• represent the coordinates of

an arbitrary point in the three coordinate systems

• are the rotation matrices and translation vectors from the left or right camera coordinate system to the global coordinate system

• are the rotation matrix and the translation vector from the left coordinate system to the right coordinate system

SYSTEM DESIGN•Each structured light sheet is regarded as

a conical surface, which can be approximated using the following conicoid equation:

•The structured light calibration procedure is followed to ascertain µ.

STRUCTURED LIGHT EXACTION AND CODING PROCEDURE•The stripes in an image can be considered

as a curvilinear structure, and the subpixel location of stripes can be obtained by the Steger’s curvilinear structure detector

•Steger’s detector and the zero-crossing detection method are integrated

•A line linking algorithm is introduced to group the subpixel points at each stripe

A. Subpixel Location Detection•Eigenvalues and eigenvectors of the

Hessian matrix :

•The subpixel location is ,

where :

A. Subpixel Location Detection•The ridges at the pixels satisfy (6). An

original image and the binary image with the marked ridge points are shown in Fig. 2(a) and (b)

A. Subpixel Location Detection•Zero-crossing detection method is

combined with Steger’s detector. Let

•A function is thus constructed as :

A. Subpixel Location Detection•If the result is , then the points

and are marked as potential ridge

points for they have different signs•Fig. 2(c) shows the marked image that

fuses Fig. 2(b) and the zero-crossing detection result

B. Linking Algorithm•From the subpixel location algorithm, the

following data are obtained for a pixel :

the orientation of the line

and the subpixel location of the line

C. Coding Procedure•To facilitate correspondence matching, the

method proposed by Gühring, which combines gray code and line shifting

•The gray code is used to design the projected

pattern such that the measurement area is divided into a large number of divisions, with each division having a unique identification code.

C. Coding Procedure•The identification code possessed by the

majority of subpixel points can be treated as that of all subpixel points at a stripe because the subpixel points at a stripe have been linked to a line.

EXPERIMENTAL RESULTS•The relative error of the conicoid method

is 0.26%, whereas the relative error of the plane method is 0.75%.

•Fig. 3(a) is an original image, whereas Fig. 3(b) is the detected result. In Fig. 3(b), some stripes are split into several segments because of discontinuities and shading.

EXPERIMENTAL RESULTS

EXPERIMENTAL RESULTS•Fig. 4(a) is an original gray code image,

whereas Fig. 4(b) is the decoding result of the gray code images

DISCUSSION AND CONCLUSION•The subpixel locations of the stripes are

detected by the proposed method as it combines the zero-crossing algorithm with Steger’s curvilinear detector

•In some applications with complicated surface shapes, the extracted center may not be the actual center, as a result of image bias.