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Guided by, 
Mrs. Alpha Vijayan 
Associative. Professor 
CSE Departement 
Presented by, 
Sam.V.Varghese (11010012) 
Sudhees...
• Reduce rise of immoral digital visual contents in 
broadcasts. 
• Motivate the research in fast and reliable obscene and...
• Manual censoring and grading in tv broadcasts and 
films. 
• IP address based filtering of internet sites. 
• Computer v...
• Difficulty in Skin and Non-skin colour separable. 
• Illumination changes over time. 
• Skin tones vary dramatically wit...
Skin colour based detection using combination of 
HSV & RGB colour space 
 Allows fast processing. 
 Robust to geometric...
• Process of finding skin-colored pixels and regions in an 
image or video. 
• Skin Detector transforms a given pixel into...
• Pixel-Based Methods 
• Classify each pixel as skin or non-skin individually, 
independently from its neighbors. 
• Color...
Automatic Detection of Human 
Body 
 Detects whether there are human immoral scenes 
present in an Image. 
 The system m...
Automatic Detection of Human 
Body (cont..) 
19 October 2014 Dept of CSE 9
• The algorithm successfully extracts 43% of the test images 
• This system is not as accurate as some recent object 
reco...
A Novel Scheme for Intelligent 
Recognition of immoral Images 
• Features extracted from skin region and whole image. 
• F...
19 October 2014 Dept of CSE 12
• Large number of pictures taken under special lighting 
• A feasible solution for the problem is to adapt the adopted ski...
 every sample skin image is first trans-formed from 
the RGB color space to the YCbCr space 
YCrCb is an encoded nonlinea...
HSV based skin detection 
• HSV skin detection : - 
• Image is converted from RGB colour space to HSV 
colour space. 
• Th...
HSV based skin detection 
19 October 2014 Dept of CSE 16
HSV based skin detection(cont..) 
19 October 2014 Dept of CSE 17
19 October 2014 Dept of CSE 18
19 October 2014 Dept of CSE 19
 The objective of this paper is to show that for every color 
space there exists an optimum skin detector scheme 
 such ...
• Hsv size gave the best performance, superior to the other 
model with less false detection 
• Hsv model gives slightly b...
comparison of 5 different color spaces HSV, 
HS,Normalized RGB and YCrCb 
HSV, HS gave the best results 
Normalized rg is ...
The project will involve building -: 
 Create a skin color/texture database 
 Extract frames from the video to get image...
1. Get the 
video/image 
Pass the video/image 
Break the video into 
images 
Mark objectionable 
Detect 
skin color 
Extra...
 Create a skin color/texture database 
 Extract frames from the video to get images that 
can be used for analysis 
 Se...
 With consistency increase growth in the immoral scenece 
market we need to stop the people to have illegal use of the it...
THANK YOU 
19 October 2014 Dept of CSE 27
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immoral scene sensoring

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describe how to sensor image base on skin detection
mainly on different skin color

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immoral scene sensoring

  1. 1. Guided by, Mrs. Alpha Vijayan Associative. Professor CSE Departement Presented by, Sam.V.Varghese (11010012) Sudheesh K.S (11010022) Tibin Thomas (11010016) Gokul G (11010021) 19 October 2014 Dept of CSE 1
  2. 2. • Reduce rise of immoral digital visual contents in broadcasts. • Motivate the research in fast and reliable obscene and immoral material filtering. • Use the power of computer vision for socially admissible projects. • Contribute to open source OpenCV library function. 19 October 2014 Dept of CSE 2
  3. 3. • Manual censoring and grading in tv broadcasts and films. • IP address based filtering of internet sites. • Computer vision based censoring.(limited) 19 October 2014 Dept of CSE 3
  4. 4. • Difficulty in Skin and Non-skin colour separable. • Illumination changes over time. • Skin tones vary dramatically within and across individuals. • Different cameras have different output for the identical image. • Movement of objects cause blurring of colours. • Ambient light, shadows change the apparent colour of the image. 19 October 2014 Dept of CSE 4
  5. 5. Skin colour based detection using combination of HSV & RGB colour space  Allows fast processing.  Robust to geometric variations of the skin patterns.  Robust to resolution changes.  Experience suggests that human skin has a characteristic colour, which is easily recognized by humans. 19 October 2014 Dept of CSE 5
  6. 6. • Process of finding skin-colored pixels and regions in an image or video. • Skin Detector transforms a given pixel into an appropriate color space . • Then use a skin classifier to label the pixel whether it is a skin or non-skin pixel. • The color needs to be represented in a color space • RGB color space ,HSV,YCrCb are common color space used to represent images. 19 October 2014 Dept of CSE 6
  7. 7. • Pixel-Based Methods • Classify each pixel as skin or non-skin individually, independently from its neighbors. • Color Based Methods fall in this category • Region Based Methods • Try to take the spatial arrangement of skin pixels into account during the detection stage to enhance the methods performance. 19 October 2014 Dept of CSE 7
  8. 8. Automatic Detection of Human Body  Detects whether there are human immoral scenes present in an Image.  The system marks skin-like pixels using combined color and texture properties. .  These skin regions are then fed to a specialized grouper, which attempts to group a human figure. 19 October 2014 Dept of CSE 8
  9. 9. Automatic Detection of Human Body (cont..) 19 October 2014 Dept of CSE 9
  10. 10. • The algorithm successfully extracts 43% of the test images • This system is not as accurate as some recent object recognition • It is detecting jointed objects of highly variable shape diverse range of poses, seen from many different camera positions. • Both lighting and background are uncontrolled previous object recognition experiments. • It might detect non humanbody whose color similar to human 19 October 2014 Dept of CSE 10
  11. 11. A Novel Scheme for Intelligent Recognition of immoral Images • Features extracted from skin region and whole image. • Fourier descriptors and signature of boundary of skin region is used as shape descriptor features. • Self Organizing Feature Maps (SOFM). • Finally, the selected features are fed to parallel classifiers • The output of each classifier is sent to decision making component. • experimental results are convincing but the results can be improved by extracting high .tp:86.7% fp:6.64% 19 October 2014 Dept of CSE 11
  12. 12. 19 October 2014 Dept of CSE 12
  13. 13. • Large number of pictures taken under special lighting • A feasible solution for the problem is to adapt the adopted skin chroma distribution • The skin tone is formed by the interaction between skin and light • Model based on Cb and Cr values can provide good coverage of all human races. • The popular skin colors of immoral images, including various lighting conditions, into several categories 19 October 2014 Dept of CSE 13
  14. 14.  every sample skin image is first trans-formed from the RGB color space to the YCbCr space YCrCb is an encoded nonlinear RGB signal, commonly used by European television studios and for image compression work. Y – Luminance component, C – Chorminance The detection rates of the immoral images and the ordinary images are 71.7% and 84.2%, 19 October 2014 Dept of CSE 14
  15. 15. HSV based skin detection • HSV skin detection : - • Image is converted from RGB colour space to HSV colour space. • The converted image is probed for the skin colours according to the H channel discription for skin colours. • The noisy image is passed through morphological filters to produce the desired image. 19 October 2014 Dept of CSE 15
  16. 16. HSV based skin detection 19 October 2014 Dept of CSE 16
  17. 17. HSV based skin detection(cont..) 19 October 2014 Dept of CSE 17
  18. 18. 19 October 2014 Dept of CSE 18
  19. 19. 19 October 2014 Dept of CSE 19
  20. 20.  The objective of this paper is to show that for every color space there exists an optimum skin detector scheme  such that the performance of all these skin detectors schemes is the same.  Used 4 color space – RGB, YCrCb, HSV, Cr Cb  Proved mathematically for the existence of optimum skin color detector using Neyman-Pearson Test 19 October 2014 Dept of CSE 20
  21. 21. • Hsv size gave the best performance, superior to the other model with less false detection • Hsv model gives slightly better performance as compared to Gaussian mixture. • It is possible that color spaces other than RGB could result in improved detection performance. 19 October 2014 Dept of CSE 21
  22. 22. comparison of 5 different color spaces HSV, HS,Normalized RGB and YCrCb HSV, HS gave the best results Normalized rg is not far behind YCrCb gave poor results 19 October 2014 Dept of CSE 22
  23. 23. The project will involve building -:  Create a skin color/texture database  Extract frames from the video to get images that can be used for analysis  Search for skin color in the image  Extract the image part with the skin color.  Shape identification  If match stop video for some minutes repeat,this after sometime 19 October 2014 Dept of CSE 23
  24. 24. 1. Get the video/image Pass the video/image Break the video into images Mark objectionable Detect skin color Extract the part with skin color in it Shape identification No Yes No end 19 October 2014 Dept of CSE 24
  25. 25.  Create a skin color/texture database  Extract frames from the video to get images that can be used for analysis  Search for skin color in the image  Extract the image part with the skin color.  Shape identification  Post on imposition  We use opencv for implementing modules 19 October 2014 Dept of CSE 25
  26. 26.  With consistency increase growth in the immoral scenece market we need to stop the people to have illegal use of the it  This tool will help them to detect and block the supply this things to the people who are not supposed to see them.  This can be also in the censer board to detect any kind of porn.  This can also be used by the parents to stop their children from watching unwanted thing without their permission or till he/she is not up to certain age limit. 19 October 2014 Dept of CSE 26
  27. 27. THANK YOU 19 October 2014 Dept of CSE 27

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