Implementation of an Object Recognizer Through Image Processing and Backpropagation Learning Algorithm

Artificial neural networks in an effort to emulate the operation of the human brain from the point of view of learning and adaptation, have evolved in such a way that different statistical and mathematical models have inspired biological models, example you have to nerve cells or better known as neurons; the same ones that are composed of dendrites which are responsible for capturing the nerve impulses emitted by other neurons. The present study aims to analyze the Backpropagation model and the multilayer topology using an object recognizer through digital image processing such as object segmentation by detection and edge determination.