FULLY SCALE AND IN-PLANE INVARIANT SYNTHETIC DISCRIMINANT FUNCTION BANDPASS DIFFERENCE OF GAUSSIAN COMPOSITE FILTER FOR OBJECT RECOGNITION AND DETECTION IN STILL IMAGES

A difficult pattern recognition problem is to recognize objects despite distortions in position, orientation and scale in cluttered backgrounds. A system capable of detecting target objects despite any kind of geometrical distortion has many potential applications since it will be able to detect target objects when the orientation and position of the target or camera is unknown. In this work we report the use of fully invariant correlation filters for object detection in still images despite any kind of geometrical distortion of the target object. A mapping technique is combined with a bandpass difference of gaussian composite correlation filter, capable of creating invariance to various types of distortion of the target object.