How to reduce an unknown size data into a fixed size data? Please read details Example:
Given n number of images marked 1 to n where n is unknown, I can calculate a property of every image which is a scalar quantity. Now I have to represent this property of all images in a fixed size vector (say 5 or 10).  

One naive approach can be this vector- [avg max min std_deviation]
And I also want to include the effect of relative positions of those images.
My approach would be using the Moments.
Using moments is a cool way trowing any arbitrary set of points into space, and it is used for both probability and mass calculations.
Since you have not stated what are you going to do with this vector representation I guess that a generalized "shape" like representation might work for you. 

If you are using Python, then this can help.