1. Image Processing: Embedding Data in Digital Images Sami Khorbotly & Firas Hasan Dept. of Elec. & Comp. Eng. & Comp. Sc. Ohio Northern University

2. Images Around Us Memories & special moments Law enforcement Biomedical field Advertisements Athletic events News & politics

3. Analog vs Digital Images Capturing Device Storage Device Display Media

4. Digital Images & Pixels A digital image is stored as a set of pixels Full image (Thousands of pixels) Subset of the image (5x5 pixels)

5. Pixels, Resolution, & Image Quality 500x500 100x100 10x10 0.25 Mega Pixels 0.1 Mega Pixels 0.1 Kilo Pixels What’s the resolution of your digital camera? Quality vs storage size trade-off.

6. Gray Scale Images A number {0-255} represents the amount of light intensity in each pixel 0 ≡ Black, 255 ≡ White, other ≡ different levels of gray

7. Color Images (RGB System) Each pixel is represented by 3 values representing red, green, and blue components. ColorRGB 25500 0 0 00 0 0 000

8. Binary Representation of Integers Decimal (base-10) number system represents numeric values using ten symbols: {0, 1, 2,…,9} Binary (base-2) number system represents numeric values using two symbols: {0, 1} DecimalBinary 1 digit 2 digits 3 digits n digits 10 10 2 10 3 10 n {0  9} {0  99} {0  999} {0  10 n -1} 222232n222232n2 {0  1} {0  3} {0  7} {0  2 n -1}

9. Decimal – Binary Conversion 3514 10 = 4x10 0 + 1x10 1 + 5x10 2 + 3x10 3 1101 10 = 1x10 0 + 0x10 1 + 1x10 2 + 1x10 3 1101 2 = 1x2 0 + 0x2 1 + 1x2 2 + 1x2 3 = 13 10 10010101 2 = 1x2 7 + 1x2 4 +1x2 2 +1x2 0 = 149 10

10. Image Storage Pixel values {0-255} Pixel values represented by 8 bits (1 byte) Gray Scale Images A pixel is represented by a single byte Example: 400x250 Image 0.1 Mega Pixels 0.1 Mega Bytes Gray Scale Images A pixel is represented by a single byte Example: 400x250 Image 0.1 Mega Pixels 0.1 Mega Bytes Color Images A pixel is represented by 3 values: R: 1 byte G: 1 byte B: 1 byte Example: 400x250 Image 0.1 Mega Pixels 0.3 Mega Bytes

11. Storage Examples 255 10 ≡ 11111111 2 0 10 ≡ 00000000 2 255 10 ≡ 11111111 2 50 10 ≡ 00110010 2 200 10 ≡ 11001000 2

12. Image Distribution & Copyrights Copying a digital image is as easy as a mouse click How do you protect the rights of the owner? What Is Copyright? According to the U.S. Copyright office * : Copyright is a form of protection provided by the laws of the United States (title 17, U. S. Code) to the authors of “original works of authorship,” including literary, dramatic, musical, artistic, and certain other intellectual works. This protection is available to both published and unpublished works. *http://www.copyright.gov

13. Copyrights (cont ed ) Who Can Claim Copyright*? The copyright in the work of authorship immediately becomes the property of the author who created the work. Only the author or those deriving their rights through the author can rightfully claim copyright. In the case of works made for hire, the employer and not the employee is considered to be the author. Infringement of Copyrights* Anyone who violates any of the exclusive rights of the copyright owner as provided by sections 106 through 122 or of the author as provided in section 106A(a), or who imports copies or phonorecords into the United States in violation of section 602, is an infringer of the copyright or right of the author. *http://www.copyright.gov

14. Copyrights (cont ed ) Remedies for infringement * An infringer of copyright is liable for either— (1) the copyright owner’s actual damages and any additional profits of the infringer, or (2) statutory damages. How can authors protect their properties? “Digital Watermarking” *http://www.copyright.gov

15. Digital Watermarking Embedding digital data into digital audio, video, or other types of signals Watermarking can be visible or invisible Visible watermarking

16. Invisible Watermarking This image is property of John Smith. All distribution rights are reserved Patient name: John Smith Birth date: Jan 1 st 1950 Blood Pressure: 135/85 Heart rate: 80

17. Different Applications Owner’s signatures (Reducing Multimedia piracy) Alert Line on TV broadcasts (Emergency public address) Time stamping of digital images Geo tagging of digital images Saving patient’s data on biomedical images

18. Visible vs Invisible Watermarks Visible watermarks are easier to temper with Invisible watermarks require overhead to be extracted

19. Invisible Watermarking Focus of this project Data must be stored (hidden) inside the picture file The quality of the picture is not to be (visibly) damaged Definitions Based on the way the watermark is applied, invisible watermarking can be categorized as follows: 1.Blind detection watermarking: Anyone who is aware of the watermarking used can recover the watermark data. 2.Non-Blind detection watermarking: only someone with the original (non watermarked) image can recover the watermark data.

20. ASCII Code & Data American Standard Code for Information Interchange Character encoding scheme Encodes 128 characters {0  127} in 7 bits each Examples o ‘A’ ≡ 65 10 ≡ 1000001 2 o ‘a’ ≡ 97 10 ≡ 1100001 2 o space ≡ 32 10 ≡ 0100000 2 o ‘/’ ≡ 47 10 ≡ 0101111 2

21. ASCII code data Property of XCo, Inc. 80 114 111 112 101 114 116 121 32 111 102 32 88 67 111 44 32 73 110 99 46 1010000 1110010 1101111 … … … 1100011 0101110

22. Embedding Data in the Image How to embed the data with minimal image error? Property of XCo, Inc. 1010000 1110010 … … 1100011 0101110 1010000 1110010 … … 1100011 0101110 1010000 1110010 … … 1100011 0101110 1010001010 11 … … 00110101110

23. Image Bit Error Effects b 7 b 6 b 5 b 4 b 3 b 2 b 1 b 0 ±1 ±2 ±4±8±16±32 ±128 ±64 Least Signif. Bit (LSB) Least Signif. Bit (LSB) Most Signif. Bit (MSB) Most Signif. Bit (MSB)

24. Error Bit Example Intended color: (100,150,200) B 0 : ±1B 1 : ±2B 2 : ±4B 3 : ±8 B 4 : ±16B 5 : ±32 B 6 : ±64 B 7 : ±128

25. LSB Watermarking Sacrifice the LSB in an image (unlikely to be noticed) Number of bits (or characters) that can be embedded is relative to the size of the image Example In a 512 x 512 image, there are 2 18 = 262,144 pixels 1.Can fit 2 18 bits (37,449 characters) in a grayscale image 2.Can fit 3x2 18 bits (112,347characters) in a color image If more space is needed, what bit will you use next? What is the cost to be paid?

26. LSB Watermarking Example Hello 245 66 62 140 214 237 35 65 89 Embed 72 101 108 108 111 Original Format Integer Format Binary Format 1001000 1100101 1101100 1101100 1101111 11110101 01000010 00111110 10001100 11010110 11101101 00100011 01000001 01011001

27. LSB Example (cont ed ) 9 bits can fit in this segment LSB marked in red 1001000 1100101 1101100 1101100 1101111 11110101 01000010 00111110 10001100 11010110 11101101 00100011 01000001 01011001 11110101 01000010 00111110 10001101 11010110 11101100 00100010 01000001 01011001 1 0 0 1 0 0 0 1 1

28. LSB Watermarking Results Watermarked 11110101 01000010 00111110 10001101 11010110 11101100 00100010 01000001 01011001 Original 11110101 01000010 00111110 10001100 11010110 11101101 00100011 01000001 01011001 245 66 62 140 214 237 35 65 89 245 66 62 141 214 236 34 65 89

29. LSB Watermarking (cont ed ) Advantages No visible damage to the watermarked image Easy to embed data and then recover it Blind detection is possible Disadvantages Watermark can be tempered with Low immunity to noise and compression

30. Spread Weighted Sum (SWS) The watermarking is applied by modifying each pixels value as follows: Where: P w :the watermarked pixel value P :the original pixel value b :the data bit to be embedded  :a constant parameter

31. SWS Watermarking Example Hello 245 66 62 140 214 237 35 65 89 Embed 72 101 108 108 111 Original Format Integer Format Binary Format 1001000 1100101 1101100 1101100 1101111 Not Needed

32. SWS Example (cont ed ) 9 bits can fit in this segment  = 5 1001000 1100101 1101100 1101100 1101111 1 0 0 1 0 0 0 1 1 245 66 62 140 214 237 35 65 89 245+5 66-5 62-5 140+5 214-5 237-5 35-5 65+5 89+5

33. SWS Watermarking Results Watermarked Original 245 66 62 140 214 237 35 65 89 250 61 57 145 209 232 30 70 94

34. Recovering Watermarks Difference between the watermarked & original images Decision based on the sign of the difference Detected watermark = [1 0 0 1 0 0 0 1 1] The value of  is a design parameter: * Large  good noise immunity, noticeable damage * Small  low noise immunity, unnoticeable damage 245 66 62 140 214 237 35 65 89 250 61 57 145 209 232 30 70 94 +5 -5 -5 -5 +5 +5

35. SWS Watermarking (cont ed ) Advantages Watermark can not be tempered with (only someone with the original image will be able to modify the watermark) Adjustable level of visible damage to the watermarked image Easy to embed data and then recover it Disadvantages Blind detection is not possible (only someone with the original image will be able to read the watermark) Adjustable immunity to noise and compression

36. Questions ?