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 Experimental results Conclusions

Introduction (1/5) Digital archive

Introduction (2/5) Uneven Illumination distribution

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

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

Introduction (5/5) The proposed scheme (Degraded Image) (Processed Image)

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

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

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

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

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

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)

Edge Detection Phase (5/5) Ex: threshold = 55 10 80 20 90 60 70 30 255 (Average Edge Image) (Edge Map) (Edge Map)

Object Classification Phase (1/3) Object detection Object 1 255 10 Object 2 Object 3 (Edge Map)

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

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

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

Text Balance Phase (2/4) Compute background Ex: 100 text 200 100 120 LIT: The light distribution image for text part N: The total number of pixels Ex: 100 text 200 100 120 140 160 180 200 (Text Part) . (Text Objects)

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

Text Balance Phase (4/4) Enhance contrast Ex: C1=30, C2=1.2 (Original) (Enhanced) Ex: 80 60 96 72 40 120 60 12 108 36 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

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

Photo Balance Phase (2/4) Enhance brightness Ex: pvi= 53, pvi is in Case3  pvi= pvi+ 25= 78 pvi : The ith pixel value (Enhanced)

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)

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

Final Phase (Balanced) (Processed Image) (Balanced)

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)

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

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

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

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

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

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

Conclusions Practical for text and text-photo images Satisfactory image quality