The way I understand your question is, why do we need to create a machine learning model when we can solve the problem using image processing techniques itself?
So It is always recommended to use image processing libraries if the objective is too simple like to find the color of some object in an image, find some template in an image invariant to rotation and scaling, edge detection etc.
But when your objective becomes complex like to identify various objects in an image, localize the object, pixel-based segmentation, video segmentation etc. You will need to go for deep learning models.
In your case, You will need to detect the car and find its color.
Let's break this down into two parts:
1) Car detection and localization:
If your test cases don't face these challenges then you can very well use image processing libraries. Else it becomes a complex process. So only way to solve this issue will be training a model with different such images.
2) Color detection
- For this, it is better to use image processing methods itself. Since for training you will need to have a significant number of images in every color you are more likely to get.
Hope this helps!