| Resumen |
So-called Vertex Chain Codes have been widely used to describe the shape of the objects. From these codes, several describing features can be obtained, e.g., the Euler characteristic. In this research, we show how Vertex Chain Codes can be used to train an Artificial Neural Network to compute the Euler characteristic of a 2-D binary image. We experimentally demonstrate how a simple linear neuron is enough to attain the goal. We present results with sets of 2-D binary images and objects of different complexity and size. |
