I've a face detection code that reads image and detects faces. The code is based on skin training where covariance and mean is calculated and skin likelihood equation is implemented on the image.
My code needs the following to be optimized and enhanced:
1- Skin likelihood threshold. I used a fixed threshold which can not detect all skin areas. To optimize I suggest using histogram on the likelihood image and calculate the threshold.
2- Region growing need to be optimized as it includes non skin areas. RGB histogram on the original should be used for region growing optimization with my existing code that check the 8-connected pixels distance.
3- Eliminates non face blobs.
4- Draw Ellipse on the center of the face blob and fill it using fillholes Aforge library which it already included.
The image data set can be downloaded from
[url removed, login to view]
In the one face folder, for example, [url removed, login to view], [url removed, login to view], [url removed, login to view], [url removed, login to view] you ca
The code is C# 2008.
Any other optimization is welcomed
Bu iş için 5 freelancer ortalamada $215 teklif veriyor
Face Recognition/Image processing Experts Here! Please contact us for more information. We can do this for you. Waiting to hear from you. Regards, Akhila ([login to view URL]).
Hi! I am willing to help u out in this project as you invited me to bid on it i want to shoe you a video demo and then if you like it we can continue contact me soon... Thanks!
HI, i have huge experience in image processing. Face and features detection in C#, Java and Python. I have Ready-made samples for your type of application too. I can optimize your code as well. Let me know if int Daha Fazla
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Hi, I would like to do this job for you! I have VS2010 but I think that this is not a problem. Could you tell me if the application is working or there are some error that is no able to run it? I converted th Daha Fazla
I have proved experience in computer vision, my time to deliver may be higher than some of the others but I like to produce high quality deliverables.