This paper presents a novel approach to feature extraction for face recognition. This approach extends a previously developed method that incorporated the feature extraction techniques of GEFE ML (Genetic and Evolutionary Feature Extraction – Machine Learning) and Darwinian Feature Extraction). The feature extractors evolved by GEFE ML are superior to traditional feature extraction methods in t...

Gabor-based face representation has achieve enormous success in face recognition. However, one drawback of Gabor-based face representation is the huge amount of data that must be stored. Due to the nonlinear structure of the data obtained from Gabor response, classical linear projection methods like principal component analysis failed to reduce this large amount of data. As a way to solve this ...

In this paper we introduce Self-Organizing Map-based techniques that can reveal structural cluster changes in two related data sets from different time periods in a way that can explain the new result in relation to the previous one. These techniques are demonstrated using a real-world data set from the World Development Indicators database maintained by the World Bank. The results verify that ...

Exploration and selection of data descriptors representing objects using a set of features are important components in many data analysis tasks. Usually, for a given dataset, an optimal data description does not exist, as the suitable data representation is strongly use case dependent. Many solutions for selecting a suitable data description have been proposed. In most instances, they require d...

Image classification is a challenging problem of computer vision. Conventional image classification methods use flat image features with fixed dimensions, which are extracted from a whole image. Such features are computationally effective but are crude representation of the image content. This paper proposes a new image classification approach through a tree-structured feature set. In this appr...

The Self-Organizing Map (SOM) is an excellent tool for exploratory data analysis. It projects the input space on prototypes of a low-dimensional regular grid which can be efficiently used to visualize and explore the properties of the data. In this article we present a novel methodology using SOM for exploratory analysis, dimensionality reduction and/or variable selection for a classification p...

This study proposes a new method of estimating fingerprint orientation field by utilizing prior knowledge of fingerprint images and Self-Organizing Map (SOM). The method is based on the assumption that fingerprint images have some common properties that can be systematized to build prior knowledge. In this method, each fingerprint image was divided into 16 regions equally and the regions were a...

A new selective attention model is proposed in this paper, which integrates a top-down attention mechanism into a bottom-up saliency map model to generate salient areas related with human interest. Human selects the certain area from natural scene and decides whether the selected area is preference or refusal. The fuzzy adaptive resonance theory (ART) network trains and memorizes the characteri...

This paper proposes a novel solution to the problem of pose estimation of three-dimensional objects using feature maps. Our approach relies on quaternions as the mathematical representation of object orientation. We introduce the rigid map, which is derived from Kohonen’s self-organizing feature map. Its topology is fixed and chosen in accordance with the quaternion representation. The map is t...