We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constellations of parts. A probabilistic representation is used for al

threshold is a key technique for the segmentation and edge detection in an image for image processing. Here in this file the threshold is on the based of the maximum entropy of an image using shannon entropy method.