Which detection algorithm will be the best for detection screws head and classify the screw types depending on the image taken for their heads only? [closed]
I'm new with opencv and computer vision and I'm working on a project for detection screws head and classify the screw types depending on the image taken for their heads only. I'm confused which detection algorithm will be the best for my project?
I need to use an appropriate computer vision detection algorithm for real-time application. There are many detection algorithms: CASCADE, CNN, F-CNN, R-FNC and so on, I'm confused which one will be the best for my project?!
If i have like this picture and i want to recognize each type of this screw head and localize them.
I appreciate your help and thank you ^_^
can you be more clear about your input, and what exactly is required from it ?
some smallish example images would help, too !
The input for the system will be a picture like this,link text which is the top view of a different type of screw and the system should be able to identify and detect these shapes.
hi, IF you have images, please upload them HERE (into your question), not on a dropbox or such, thank you.
HELLO, SORRY FOR THAT.
i do not think, we can answer your question.
while you're safe to rule out cascade classifiers (which only can detect one class at a time), we cannot help you choose a deep learning architecture (pretty much beyond the scope of opencv)
also, your image is useless, as it is computer-generated, and does not show any real world problems, like variations in pose / lighting / reflections
imho, you shuld get a few hundred * real world* images for each class, and try to retrain something, using the idea you best understood so far.