Graphic information processing using intelligent algorithms

Finding an appropriate set of features is an essential problem in the design of a shape recognition system. This paper attempts to show that for recognition of objects with high shape variability such as handwritten characters and human faces it is preferable to use the modified artificial neural network to feed the system with processed images by novel scale-and rotation-invariant interest point detectors and descriptors and to rely on learning to extract the right set of features. Experiments have confirmed the usefulness of the modified artificial neural network in a real-world application.