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Hi, I want to train svm to detect each type of these road signs. I need some advice about training.

1. Should I use 3-channel positive images for training or can I use grayscaled images? ( if both, what's the difference in accuracy then?)
2. How many positives should I have in your opinion for each sign to train a good classifier? (These signs are very similar so it's gonna be tough to predict it well, Am I right?)
3. Maybe other methods can do better like BOW or KNN?

Hi, I want to train svm to detect each type of these road signs. I need some advice about training.

1. Should I use 3-channel positive images for training or can I use grayscaled images? ( if both, what's the difference in accuracy then?)then?)
2. How many positives should I have in your opinion for each sign to train a good classifier? (These signs are very similar so it's gonna be tough to predict it well, Am I right?)
3. Can I use 30x30 images or they are too small?
4. Maybe other methods can do better like BOW or KNN?

Hi, I want to train svm to detect recognize each type of these road signs. I need some advice about training.

1. Should I use 3-channel positive images for training or can I use grayscaled images? ( if both, what's the difference in accuracy then?)
2. How many positives should I have in your opinion for each sign to train a good classifier? (These signs are very similar so it's gonna be tough to predict it well, Am I right?)
3. Can I use 30x30 images or they are too small?
4. Maybe other methods can do better like BOW or KNN?