Clasificador para la detección de personas desnudas en imágenes

images constitute an essential component within the digital contents generated and interchanged through telecommunication networks. since some years ago, the international community has been working in various filtering and contents classification systems. within these systems, the evaluation of the images plays a crucial role. in this work, the main results are presented in relation to the design, implementation and testing of an image classification module, whose first task is to detect naked people. this module, mlp (multilayer perceptron) neural networks based, achieves elevated detection levels, which along to its velocity and easy development, turns it into a serious alternative for its inclusion in content filtering software.