Optical Design for Automatic Identification

Transcription

1 s for Automatic Identification s design tutors: Prof. Paolo Bassi, eng. Federico Canini cotutors: eng. Gnan, eng. Bassam Hallal

2 Outline s design 4 design

3 Outline s design 4 design

4 s : new Techniques to improve Auto ID systems Performance Possible applications: design Optical systems to be designed of a Barcode Reader, i.e.:

5 s s Characterization (SAFARILAB) to measure the system Spatial Frequency Response, SFR Optical Level Optimization (OLOM) to optimize the optical part of the imaging system (lens) design Level Analysis and to analyze and optimize the Optimization (SLALOM) whole imaging system (lens, electronics, detector) s to optimize a freeform lens that used with a LED produces a custom illumination design to optimize a diffractive optics that used with a LASER produces the desired pattern

6 Outline s design 4 design

7 s characterization: Spatial Frequency Response measurement (SFR = F [PSF]) design Edge Source: Slanted edge to avoid sampling effect (dependency on pixel array alignment wrt the edge)

8 s design Software: calculates SFR from a slanted edge image follows the ISO standard reduces the noise that affects the measurement Measurement set up:

9 s SaFaRiLAB vs Imatest and ImageJ: design SaFaRiLAB: comparable with other available softwares

10 s Noise reduction: SFR 0.4 design Normalized spatial frequency 2 Strong reduction of noise that affects the measurement

11 s Optical Level Optimization (OLOM) : able to optimize at Optical Level (just lens) an imaging system with SFR invariance as Cubic Phase Mask (CPM) SFR design Normalized spatial frequency

12 s Optical imaging system design (in ZEMAX): already designed lens optimization of α in cubic phase mask using (CPM = f (x, y ) = α(x 3 + y 3 )) ORIGINAL LENS design C P M S T O P S T O P C C D S E N S O R

13 s Performance design evaluation: minimum resolving power [Mils] design SFR R =minimum resolution M = magnification 0.5 threshold (th) 0.25 frequency limit (fth) Normalized spatial frequency 1

14 s Performance without CPM vs with CPM and MEASURED vs DESIGNED: the CPM extends the Depth Of Field (DoF); measured and designed results are comparable mils mils design 13 mils 0 NOCPM DESIGNED NOCPM MEASURED CPM DESIGNED CPM MEASURED Object Distance [mm]

15 s design Level Analysis and Optimization () : able to optimize and analyze at Level (lens, electronics decoder) an imaging system with SFR invariance

16 s design Level Analysis and Optimization () : (a) O-, (b) A-

17 s Optical imaging system design (in ZEMAX): Two possible design for adding a quartic contribution to an original lens: First Design : change of a surface of the original lens Second Design : addition of a lens with a quartic surface starting design optimized by optimization of the quartic surface using SLA L OM design ORIGINAL LENS Second Design S T O P S T O P First Design C C D S E N S O R

18 s First Design: before and after using SLA L OM DEC DEC FAIL FAIL Object Distance [mm] Object Distance [mm] Second Design: before and after using SLA L OM DEC DEC FAIL FAIL design Object Distance [mm] Object Distance [mm]

19 Outline s design 4 design

20 s design for a Custom Illumination: limited into a desired area and with more light along the area edges (compensation for sensor light losses) implementation (in MATLAB) of a software for optimization of the free-form lens coefficients z = f (x, y ) = c1 x 2 + c2 y 2 + c3 x 4 + c4 x 2 y 2 + c5 y 4 + c6 x 6 + c7 x 4 y 2 + c8 x 2 y 4 + c9 y 6

21 s Surface measurement of the lens Free-Form prototype: design Good agreement between measured and designed surface

22 s Irradiance profile measurement: design Good agreement between irradiance profile of free-form lens DESIGNED and MEASURED

23 design * s Problem: to design a Diffractive Optical Element, DOE that with a LASER produces a large Field Of View, FoV (not paraxial hypothesis). FOV = 40 LASER DOE design Image * developed at Friedrich-Alexander University, Erlangen, DE

24 design s Starting point: Iterative Fourier Transform Algorithm (IFTA) that assumes paraxial approximation. DOE* Projection (CGH plane) (image plane) f * ( x, y ) design Amplitude Constraint: f * = exp( j arg( f )) F (ν x,ν y ) Amplitude Constraint: F * = Fdes exp( j arg( F )) DOE Projection* (CGH plane) (image plane) f ( x, y ) Y F * (ν x,ν y )

25 design s Solution: predistortion of desired image considering the effects caused by non paraxial angle assumption. blue line: desired image (little square at 20, big square at 40 ); red line: predistorted desired image design

26 design s design Patterns generated by DOEs designed with and without Paraxial Approximation Compensation:

27 design s FoV measurement: 300 CPA design SPEC x[mm] PA z[mm]

28 Outline s design 4 design

29 s s Characterization (SAFARILAB) able to measure imaging systems performance Optical Level Optimization (OLOM) provides a starting point optical design for the whole system optimization Level Analysis and provides a whole optimized Optimization (SLALOM) system design s freeform lens optimized to obtained the desired illumination design DOE optimized to obtained the desired pattern

30 s design THANKS FOR YOUR ATTENTION!