A Feature Extraction Algorithm Based on Optimal Neighborhood Size

Automatic Sharp Feature Extraction from Point Clouds with Optimal Neighborhood Size

A novel algorithm is proposed for extracting sharp features automatically and at optimal scale from point clouds. First, the vector between a given point and the centroid of its neighborhood at a given scale is projected on the normal at this point. This projection is called the ’projected distance’ at this point. The projected distance and surface normal vector are recalculated at several scal...

A Hybrid Feature Selection Algorithm Based on Large Neighborhood Search

A RELIEF Based Feature Extraction Algorithm

RELIEF is considered one of the most successful algorithms for assessing the quality of features due to its simplicity and effectiveness. It has been recently proved that RELIEF is an online algorithm that solves a convex optimization problem with a marginbased objective function. Starting from this mathematical interpretation, we propose a novel feature extraction algorithm, referred to as LFE...

A Chinese Product Feature Extraction Method Based on KNN Algorithm

The product feature set of online reviews obtained by the current product feature extraction methods has a low coverage rate of review information. In order to solve this problem, this paper proposes a method of product feature extraction based on KNN algorithm. We establish the classification system of product feature set firstly. Then we extract part of product features as training set manual...

Determining optimal window size for texture feature extraction methods

This paper presents a technique to determine optimal window sizes for the computational methods utilized to extract features from textured images. Those features are useful for both texture classification and segmentation. Window sizes are determined in order to outperform two complementary tasks, namely, texture feature evaluation and texture segmentation, which have opposite requirements. Thu...