Could anyone suggest the best algorithm for a real-time Car recognition (say in a parking space)? I am planning to implement the same on FPGA as well. Kindly suggest. Thank you.
Do you mean car detection or recognition? Detection: where are all the cars? Recognition: which car is this? See: Object detection versus object recognition
In any case, the short form of the answer is to prototype the heck out of this, likely using OpenCV or libccv, your favorite neural network package, and as much horsepower as possible (several Nvidia GTX 980). Don't worry about realtime-ness or implementation details, just get it working first. The state of the art for object recognition and detection both is probably convolutional neural networks, check out stuff like AlexNet; there are simpler algorithms (eg Histogram of Oriented Gradient or HoG) which could do okay at detection, but not at recognition (there is a decent person detector using HoG, I think you can probably make a decent car detector in the same way).
Running this on a FPGA is... unlikely: high-end desktop GPUs are very well suited to the problem, and orders of magnitude faster at it. People are working on neural network ASICs now, should be ready in a couple of years.
Try ISM : Implicit shape models