EC.Engineer
Junior Member level 1
Hi all,
I am looking for some help to develop a face detection and recognition program on PIC32. I tried using the OV9650 camera but it did not work so now I am using the µCAM-TTL from 4D systems.
The problem is, the PIC has very limited RAM and using RAW images seems very difficult as the lowest size of 80x60 pixels is taking more than 4kb RAM. Moreover, the image quality is so poor that even manual face recognition by ourselves looks difficult.
If I try to increase the image size then the PIC won't be able to handle that data.
But if I read the image in JPEG format from µCAM module then I can use a larger image in smaller kb size.
Now, are there any source codes available for face detection from JPEG images? There's a published paper by **broken link removed** but I can't seem to find any functions and source files.
Can anyone help? I can convert the codes from most of the programming languages to mikroC for my use as long as they are portable. Even algorithms might help, if they are properly explained.
Thanks
I am looking for some help to develop a face detection and recognition program on PIC32. I tried using the OV9650 camera but it did not work so now I am using the µCAM-TTL from 4D systems.
The problem is, the PIC has very limited RAM and using RAW images seems very difficult as the lowest size of 80x60 pixels is taking more than 4kb RAM. Moreover, the image quality is so poor that even manual face recognition by ourselves looks difficult.
If I try to increase the image size then the PIC won't be able to handle that data.
But if I read the image in JPEG format from µCAM module then I can use a larger image in smaller kb size.
Now, are there any source codes available for face detection from JPEG images? There's a published paper by **broken link removed** but I can't seem to find any functions and source files.
Can anyone help? I can convert the codes from most of the programming languages to mikroC for my use as long as they are portable. Even algorithms might help, if they are properly explained.
Thanks