Title :
Classification and Segmentation of Visual Patterns Based on Receptive and Inhibitory Fields
Author :
Fernandes, Bruno J T ; Cavalcanti, George D C ; Ren, Tsang I.
Author_Institution :
Inf. Center, Fed. Univ. of Pernambuco, Recife
Abstract :
This paper presents a new model to realize a supervised image segmentation task. It is based on the concept of receptive fields that intends to analyze pieces of an image considering not only the pixels or group of them, but also the relationship between them and their neighbors, called segmentation and classification with receptive fields (SCRF). Also, in order to work with the SCRF model, is proposed here a new artificial neural network, called IPyraNet, which is a hybrid implementation of the recently described PyraNet and the nonclassical receptive fields inhibition. Furthermore, the model and the network are applied together in order to realize a satellite image segmentation task.
Keywords :
image classification; image resolution; image segmentation; neural nets; IPyraNet; artificial neural network; supervised image segmentation; visual pattern classification; visual pattern segmentation; Artificial neural networks; Feature extraction; Hybrid intelligent systems; Image analysis; Image recognition; Image segmentation; Informatics; Neural networks; Pixel; Skin; Image classification; Image segmentation; Neural network; Pattern recognition;
Conference_Titel :
Hybrid Intelligent Systems, 2008. HIS '08. Eighth International Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-0-7695-3326-1
Electronic_ISBN :
978-0-7695-3326-1
DOI :
10.1109/HIS.2008.42