We present a local density estimator based on first order statistics. To estimate the density at a point, x, the original sample is divided into subsets and the average minimum sample distance to x over all such subsets is used to define the density estimate at x. The tuning parameter is thus the number of subsets instead of the typical bandwidth of kernel or histogram-based density estimators....

with 3 edits (delete the C, delete the last A and insert a C). This is the best that can be done so the minimum edit distance is 3. The MED problem is an important problem that has many applications. For example in version control systems such as git or svn when you update a file and commit it, the system does not store the new version but instead only stores the “difference” from the previous ...

In this paper, through a series of specific examples, we illustrate some characteristics encountered in analyzing high dimensional multispectral data. The increased importance of the second order statistics in analyzing high dimensional data is illustrated, as is the shortcoming of classifiers such as the minimum distance classifier which rely on first order variations alone. We also illustrate...

In this work, a novel solution to the speaker identification problem is proposed through minimization of statistical divergences between the probability distribution (g) of feature vectors from the test utterance and the probability distributions of the feature vector corresponding to the speaker classes. This approach is made more robust to the presence of outliers, through the use of suitably...

Potato image segmentation is an important part of image-based potato defect detection. This paper presents a robust potato color image segmentation through a combination of a fuzzy rule based system, an image thresholding based on Genetic Algorithm (GA) optimization and morphological operators. The proposed potato color image segmentation is robust against variation of background, distance and ...

In this paper, we present an automated face recognition (AFR) system that contains two components: eye detection and face recognition. Based on invariant radial basis function (IRBF) networks and knowledge rules of facial topology, a hybrid neural method is proposed to localize human eyes and segment the face region from a scene. A dual eigenspaces method (DEM) is then developed to extract alge...

Biometric identification technology has been associated generally with very costly top secure applications. In this paper, we suggest a new approach to iris recognition system. Morphological operators are used for iris edge detection. Simplicity and quickness of proposed edge detection method which is coping with binary images is considerable. Binary code representation via phase of Daubechies ...

In this paper we implement and test the recently described nearest subspace classifier on a range of microarray cancer datasets. Its classification accuracy is tested against nearest neighbor and nearest centroid algorithms, and is shown to give a significant improvement. This classification system uses class-dependent PCA to construct a subspace for each class. Test vectors are assigned the cl...

In this paper, we propose a new object classification technique based on polygonal approximation of the open profile of object. The vertices of polygonal approximation are formed by high curvature points of the profile and they are selected by Fourier transform of the object contour. A series of features are computed from the polygonal approximation and then the minimum distance classifier is u...