1 / 35

Omer Barkol joint work with Hadas Kogan, Doron Shaked and Mani Fischer HP Labs, Israel

A Robust Similarity Measure For Automatic Inspection. Omer Barkol joint work with Hadas Kogan, Doron Shaked and Mani Fischer HP Labs, Israel September 2010. THE CHALLENGE. Print-inspection of print-speed variable-data input Compare two images from different acquisition devices

joey
Download Presentation

Omer Barkol joint work with Hadas Kogan, Doron Shaked and Mani Fischer HP Labs, Israel

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. A Robust Similarity Measure For Automatic Inspection Omer Barkol joint work with Hadas Kogan, Doron Shaked and Mani Fischer HP Labs, Israel September 2010

  2. THE CHALLENGE Print-inspection of print-speed variable-data input Compare two images from different acquisition devices Dissimilarities to ignore: color, spatial deformation Avoid false alarms Scanner Digital Reference Scanned Image Reference Image

  3. Inspection DEMOED @ IPEX 2010 Capability demonstrated on Indigo-7500 press

  4. SIMILARITY MAP reference similarity map scan

  5. SIMILARITY MAP Sub-pixel misregistration Locally varying reference similaritymap scan

  6. GOAL: Improved similarity measure – insensitive to (locally varying) sub-pixel misregistration Digitalreference Scannedimage

  7. SP SIMILARITY MEASURE “Definition”: SM(x,y) respects convex combinations if for any 0≤a≤1, SM(x,y) ≤ SM(x,ax+(1-a)y) ax+(1-a)y y x 9 2 ) + ( ) = ( 11 11 • 100 90 0 100 200 • 90 100 110

  8. SP SIMILARITY MEASURE Let SM be a similarity measure that respects convex combinations Let x’ is the patch x shifted by 1 pixel and GSM(x)=SM(x,x’) GSM(x)=minx’ in Nx(SM(x,x’)) x’ x Recall: GSM(x) = SM(x,x’) ≤ SM(x,ax+(1-a)x’)= SM(x,y) y Then define SPSM(x,y) = SM(x,y) / GSM(x) min(1,SM(x,y)/GSM(x))

  9. structure luminance contrast Shift by 0.5 pixel + 3 defects Original image SSIM result EXISTING SIMILARITY MEASURE • SSIM (Structure SIMilarity measure) – • State-of-the-art image measure that reflects human perception Sensitive to sub-pixel misregistration Use SPSSIM PROBLEM: SSIM does not respect convex combinations * Z. Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simoncelli. Image quality assessment: From error visibility to structural similarity. IEEE Transactions on Image Processing, 13:600–612, 2004.

  10. structure luminance contrast EXISTING SIMILARITY MEASURE ax+(1-a)y y x might be negative

  11. inner product REVISED SIMILARITY MEASURE respects convex combinations

  12. SPSSIM SIMILARITY MEASURE SPSM SPSM We then define

  13. SPSSIM - RESULTS Shift by 0.5 pixel + 3 defects Originalimage SSIMresult SPSSIMresult

  14. SPSSIM - RESULTS Reference Scan SSIM SPSSIM

  15. SPSSIM - RESULTS False alarm 2-D sub-pixel shift SPSSIM False alarms rate original SSIM ~ SSIM Miss detection random Miss detections rate

  16. RECAP ON SPSSIM • Introducing two contributions: • Revise SSIM to respect convex combinations • Define a new paradigm SPSM creating SPSSIM

  17. Any questions?

  18. INSPECTION HARDWARE Overview Duplex and Variable resolution Scanners GPU enhanced computing

  19. INSPECTION SOFTWARE OVERVIEW Press GUI print configuration results CMYK reference iDo Vcorn XML XML iVision Orchestrator images ILS Scanners RGB scans Inspection config images File system inspect

  20. INSPECTION SYSTEM OVERVIEW AviMalki Nechama, Yair, Silvia Ofer,Anna Press Leonid, Alex, Andrey GUI print configuration iDo Vcorn iVision Michael, Nataly, Lena Orchestrator ILS Scanners Rodolfo Inspection HPLI File system inspect

  21. CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze Hadas Mani Hadas Marie Sagi Sagi Marie Mani CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze INSPECTION: HIGH LEVEL COMPONENTS Press Hadas, Doron,Mani iVision CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze Alex Carl Michal inspection GPU Image Saving Distributed multi-threaded with GPU part

  22. CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze INSPECTION: HIGH LEVEL COMPONENTS Press iVision CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze inspection GPU Image Saving

  23. Reference INPUT IMAGES CMYK 203.2x81.28 dpi Scans RGB 200x80 dpi The Job 812.8 dpi

  24. CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze INSPECTION: HIGH LEVEL COMPONENTS Press iVision CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze inspection GPU Image Saving

  25. CMYK to RGB 7x7x7x7 Conversion table

  26. CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze INSPECTION: HIGH LEVEL COMPONENTS Press iVision CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze inspection GPU Image Saving

  27. Registration initial scale final color and size adjustments initial scale scale and offset crude affine transform adjustments

  28. CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze INSPECTION: HIGH LEVEL COMPONENTS Press iVision CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze inspection GPU Image Saving

  29. Bands & streaks bands streaks dust streaks

  30. CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze INSPECTION: HIGH LEVEL COMPONENTS Press iVision CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze inspection GPU Image Saving

  31. CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze INSPECTION: HIGH LEVEL COMPONENTS Press iVision CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze inspection GPU Image Saving

  32. ANALYSIS Ignore faint / thin / small blobs find strong blobs and combine close ones report on original locations original reference original scan SPSSIM map

  33. CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze INSPECTION: HIGH LEVEL COMPONENTS Press iVision CMYK 2 RGB Registration Color Monitoring Bands, streaks & dust streaks Compare: SPSSIM Analyze inspection GPU Image Saving

  34. OUTPUT

  35. FUTURE • Enhance robustness to different spatial deformation • Collect trends in a series of images • Allow inspection to give automatic feedback to the machine – self repair

More Related