Abstract
Applications of independent component analysis (ICA) to feature extraction have been a topic of research interest. Here, we propose a novel recognition method using features extracted by ICA. The proposed method consists of some modules for each category and a synthesizer. A module has a feature extraction and a classification. Features are independent components extracted by ICA algorithm using the training data for each class and classification are made by these features. These output of the module are combined and categories are decided by a majority rule. We evaluate the performance of the proposed method for several recognition tasks. From these results, we confirm the effectiveness of the recognition method using independent components for each class.
