I am new to AI/ML and am trying to use the same for solving the following problem. I have a set of (custom) images which while having common characteristics also will have a unique pattern/signature and color value. What set of algorithms should I use to have the pass in following manner: 1. Recognize the common characteristic (like the presence of a triangle at any position in a 10x10mm image). If present, proceed, else exit. 2. Identify the unique pattern/signature to identify each image individually. The pattern/signature could be shaped (visible to the human eye or hidden like using an overlay shape using the background image with no boundaries). 3. Store color tone/hue/saturation to determine any loss/difference (maybe because the capture source is different from the original one).
While this is in a way similar to face recognition algorithm, for me saturation/shadow will matter while being direction independent.
I figure that using CNN may be the way to go for step#2 and SVN for step#1, any input on training, specifics will be appreciated. What about step#3, use BGR2HSV? The objective is to use ML/AI and not get into machine-vision.