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A Hybrid Strategy for Improving Illumination-Balance of Degraded Text-Photo Images

A Hybrid Strategy for Improving Illumination-Balance of Degraded Text-Photo Images. Chair Professor Chin-Chen Chang Feng Chia University National Chung Cheng University National Tsing Hua University http://msn.iecs.fcu.edu.tw/~ccc. Outline. Introduction The proposed scheme

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A Hybrid Strategy for Improving Illumination-Balance of Degraded Text-Photo Images

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  1. A Hybrid Strategy for Improving Illumination-Balance of Degraded Text-Photo Images Chair Professor Chin-Chen Chang Feng Chia University National Chung Cheng University National Tsing Hua University http://msn.iecs.fcu.edu.tw/~ccc

  2. Outline • Introduction • The proposed scheme • Experimental results • Conclusions

  3. Introduction (1/5) • Digital archive

  4. Introduction (2/5) • Uneven Illumination distribution

  5. Introduction (3/5) • Text image balance scheme (Degraded Image) (Processed Image)

  6. Introduction (4/5) • Text-photo image? (Text-photo Image)

  7. Introduction (5/5) • The proposed scheme (Degraded Image) (Processed Image)

  8. Flowchart (Photo Part) (Balanced) (Degraded Image) (Processed Image) (Text Part) (Balanced)

  9. Four Phases of Proposed Scheme • Edge Detection Phase • Object Classification Phase • Text Balance Phase • Photo Balance Phase

  10. Edge Detection Phase (1/5) • Sobel edge detection (Detector (1). 0°) (Detector (2). 45°) (Detector (3). 90°) (Detector (4). 135°)

  11. Edge Detection Phase (2/5) • Ex. 1: Edge area (Detector (1). 0°) (Original Image) (20×-1) + (10×0) + (90×1) + (20×-2) + (10×0) + (90×2) + (20×-1) + (10×0) + (90×1) = 280

  12. Edge Detection Phase (3/5) • Ex. 2: Smooth area (Detector (1). 0°) (Original Image) (20×-1) + (10×0) + (10×1) + (20×-2) + (10×0) + (10×2) + (20×-1) + (10×0) + (10×1) = 40

  13. Edge Detection Phase (4/5) • Average edge image Edge Image 0° Edge Image 45° Edge Image 90° Edge Image 135° + + + = 4 (Average Edge Image) • Edge map ＞Threshold  edge (255) ≦ Threshold  non-edge (0)  (Average Edge Image)

  14. Edge Detection Phase (5/5) • Ex: threshold = 55 (Average Edge Image) (Edge Map) (Edge Map)

  15. Object Classification Phase (1/3) • Object detection Object 1 Object 2 Object 3 (Edge Map)

  16. Object Classification Phase (2/3) • Mark square areas (Edge Map) (Objects)

  17. Object Classification Phase (3/3) • Classification according to object size (Text Part) (Photo Part)

  18. Text Balance Phase (1/4) • Flowchart (Processed Text Image) (Light Distribution Image)

  19. Text Balance Phase (2/4) • Compute background LIT: The light distribution image for text part N:The total number of pixels • Ex: (Text Part) . . . (Text Objects)

  20. Text Balance Phase (3/4) • Illumination Balance (LIT) (Original Image) (Balanced Image) • Ex: bf = 230 bf : The bright factor Oi: The ith pixel of original image BI : The balanced image

  21. Text Balance Phase (4/4) • Enhance contrast (Original) (Enhanced) • Ex: 80 60 96 72 BI: Balanced image C1, C2: Contrast parameters C1=30, C2=1.2 (40 – 30) × 1.2 = 12 (120 – 30) × 1.2 = 108 (60 – 30) × 1.2 = 36

  22. Photo Balance Phase (1/4) • Purpose (Degraded Image) (Processed)

  23. Photo Balance Phase (2/4) • Enhance brightness • Ex: pvi= 53, pviis in Case3 •  pvi= pvi+ 25= 78 pvi: The ithpixel value (Enhanced)

  24. Photo Balance Phase (3/4) • Enhance the contrast of each photo object A dynamic histogram equalization scheme (2007) (Object 1) (Object 2) (Object 1 processed) (Object 2 processed)

  25. Photo Balance Phase (4/4) • Ex: histogram equalization Contrast Enhancement (Object 1) (Object 1 processed) (Original histogram) (Contrast enhanced)

  26. Final Phase (Balanced) (Processed Image) (Balanced)

  27. Experimental Results (1/7) • Scanned Images • Artificial Scanned-Liked Image 512×512 pixels VLB:S.C. Hsia and P.S. Tsai (2005) LLB:S.C. Hsia, M.H. Chen and Y.M. Chen(2006)

  28. Experimental Results (2/7) • Scanned text-photo images 1 2 • The degraded image • VLB • LLB • The proposed scheme 3 4

  29. Experimental Results (3/7) • Scanned text images 1 2 • The degraded image • VLB • LLB • The proposed scheme 3 4

  30. Experimental Results (4/7) • Scanned-liked images (Original Image) (Scanned-liked Image)

  31. Experimental Results (5/7) • Scanned-liked text-photo images 1 2 • The Scanned-liked Image • VLB • LLB • The proposed scheme 3 4

  32. Experimental Results (6/7) • Scanned-liked text images 1 2 • The Scanned-liked Image • VLB • LLB • The proposed scheme 3 4

  33. Experimental Results (7/7) • Compute PSNR values Scanned-liked text images Scanned-liked text-photo image

  34. Conclusions • Practical for text and text-photo images • Satisfactory image quality

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