Face Morphing

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Developed software that contains a database of several faces with functionality of combining various facial features. The software altered a few original characteristics of the image to produce a new face that looked very natural. Project developed using visual C++.

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Face Morphing

  1. 1. FACE MORPHING PROJECT GUIDE: PRESENTED BY: Prof. Ms. Ibtisam Mogul Abhinav Mehrotra Akshay Suresh Karan Modi
  2. 2. What is Digital image processing ??? •Digital Image Processing refers to processing digital images by means of a digital computer. •Digital computer or imaging machines can operate on images generated by sources such as ultra sound, electron microscopy and computer generated images. •Thus digital image processing encompasses a wide and varied field of applications.
  3. 3. Digital Image processing can be considered to be comprised of 3 types of computerized process:  Low level processing  Mid-Level Processing  Higher level processing
  4. 4. INTRODUCTION TO OUR TOOL Project includes: • A collection of faces divided into three parts • User interface to select parts of different faces • Image Processing functionality to combine selected parts of various faces.
  5. 5. EXISITING SYSTEM WE ARE TRYING TO BETTER • Traditional system directly marks control points. • Face Morpher guesses basic spots - expensive software. • Alternative method of morphing-using Mosaicking-less expensive.
  6. 6. PROJECT PURPOSE • COSMETIC SURGERY • BARBER SHOPS • DETECTIVE AGENCIES AND POLICE
  7. 7. FUNCTIONALITY • Expansion and Contraction of images. • Histogram Specification of the image. • Combining the image. • Blurring the edges. • Displaying the images.
  8. 8. INFORMATION FLOW CONTRACTION & IMAGE FILES EXPANSION OF IMAGES HISTOGRAM SPECIFICATION FACE SYNTHESIS COMBINING TOOL PROCESSED IMAGES BLURRING THE EDGES DISPLAY IMAGE CUSTOMIZE & DISPLAYING THE CUSTOMIZED IMAGE
  9. 9. EXPANSION & CONTRACTION • Needed to equalize the width of different parts of the face. • Expansion or contraction is done in two cases: 1. When the parts are selected to combine. 2. To customize the combined face.
  10. 10. CASE 1 The width of all the parts is expanded to the width of widest part in the triplet
  11. 11. CASE 2 It is done by entering the % of expansion
  12. 12. CALCULATION OF PIXEL COLOR • To contract a 500x500 image into a 300x300 image, we reduce the pixel spacing. • Any compressed pixels falls somewhere in the middle of the four neighboring pixels. Contd….
  13. 13. Contd.. a1=b*m+a*(1-m) • We use interpolation m 1-m a b In x-direction c d In y-direction c1 =d*m+c*(1-m) a1 n The color of the target pixel is : 1-n c1 a1*(1-n)+c1*n
  14. 14. HISTOGRAM SPECIFICATION • HISTOGRAM: Histogram is defined as probability of occurrence of each intensity level in the image. • HISTOGRAM SPECIFICATION: The method used to generate a processed image that has a specified Histogram is called Histogram Specification.
  15. 15. » Contd.. • Histogram does not tell about location of pixels. • In Histogram equalization, we pick up all the pixels at one particular intensity level and throw it at some other intensity level. • Histogram Equalization thus provides an image whose gray levels are evenly distributed throughout the image.
  16. 16. HISTOGRAM SPECIFIED IMAGES
  17. 17. COMBINING • Minimize edge formation of point of combining two images. • Assume predetermined overlap limit, determining thickness of edge at overlap.
  18. 18. • All the three parts are combined when the user clicks on the combine button.
  19. 19. BLURRING THE EDGES
  20. 20. CONTD..
  21. 21. DATA FLOW DIAGRAM LEVEL 0 Images of Image Files Face Parts Image Processing Edited Face Unit Image Display Unit
  22. 22. DATA FLOW DIAGRAM LEVEL 1 Images of parts of Face Raw Image Parts Size Parts Adjustmen having t same size Parts with Image Similar intensity Standardization Merging Edited Images Image Display Unit
  23. 23. • The photographs are to be taken in a very standard manner with the nose in the centre and probably without any expressions on the face. • Only color images have been considered.
  24. 24. • An effective face editing tool • Uses Digital Image processing
  25. 25. THANK YOU !

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