CODEWITHSUNDEEP
imageopenglopencvimage-processing
ssaaddii
ssaaddii

Reputation: 81

Face matching after detection

I am working on a software that will match a captured image (face) with 3/4 images (faces) of same person. Now there are 2 possibilities

1- That the captured image (face) is of the same person whose 3/4 images (faces) are already stored in database
2. Captured image is of a different person

Now i want to get the results of the above 2 scenarios, i.e matched in case 1 and not matched in case 2. I used 40 Gabor filters so that i can get good results. Moreover i get the results in an array (histogram). But It don't seems to work fine and environment conditions like light also have influence on the matching process. Can any one suggest me a good and efficient technique for this thing to achieve.

Upvotes: 4

Views: 272

Answers (1)

Saikat
Saikat

Reputation: 1219

Well, This is basically face identification problem.

You can use LBP(Local Binary Pattern) to extract features from images.LBP is very robust and llumination invariance method.

You can try following steps-

Training:-

  1. Extract face region (using OpenCV HaarCascade)
  2. Re-size all the extracted face regions to equal size
  3. Divide resized face into sub regions(Ex: 8*9)
  4. Extract LBP features from each region and concatenate them, , because localization of feature is very important
  5. Train SVM by this concatenated feature, with different label to each different person's image

Testing:-

  1. Take a face image and Follow step 1 to 4
  2. Predict using SVM(about which person's image this is)

Upvotes: 2

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