For improved multispectral classification and retrieval of Lambertian reflectances from patches of arbitrary surface orientation, we investigate the consequences of a dichromatic illumination model accounting for direct sunlight and diffuse skylight. This illumination model leads to the concept of spectral classes as two dimensional planes in the feature space. This paper addresses three questi...

The MML classification program, Snob, deals with mixture modelling (or clustering) of circular data. It has recently been extended to do Markov modelling of the serial correlation between clusters such as modelling the fact that a Helix cluster favours being followed by another Helix cluster. Such a model is better known as a Hidden Markov Model. The search for the most appropriate secondary st...

A digitizing tablet was employed to collect handwritten signatures with five quantities recorded, namely horizontal and vertical pen tip position, pen tip pressure, and pen azimuth and altitude angles. Cluster analysis was applied to segment the feature space into sub-regions of “similar” signatures to facilitate the classification and verification tasks. Both problems were solved with the use ...

The recognition of emotional information is a key step toward giving computers the ability to interact more naturally and intelligently with people. This paper presents a completely automated real-time system for facial expression’s recognition based on facial features’ tracking and a simple emotional classification method. Facial features’ tracking uses a standard webcam and requires no specif...

In this research, a new method for automatic detection and classification of suspected breast cancer lesions using ultrasound images is proposed. In this fully automated method, de-noising using fuzzy logic and correlation among ultrasound images taken from different angles is used. Feature selection using combination of sequential backward search, sequential forward search and distance-based m...

Abstract — This paper presents an algorithm for feature extraction from a bark image set based on parameter of generalized Gaussian density (GGD) model and color angles in different color space. The extracted features such as the scale parameter and the shape parameter of GGD for image will be employed for classification. The radial basis probabilistic neural networks (RBPNN) and supporting vec...

The paper gives an introduction to parallel discrete event simulation (PDES) and emphasising the classification of the research done in the area. Such a classification includes a time line presentation of different streams of thought in the field and research from different angles. In this respect four synchronisation streams including conservative, optimistic, hybrid and adaptive protocols are...

We consider the problem of learning with instances defined over a space of sets of vectors. We derive a new positive definite kernel f(A,B) defined over pairs of matrices A,B based on the concept of principal angles between two linear subspaces. We show that the principal angles can be recovered using only inner-products between pairs of column vectors of the input matrices thereby allowing the...

In this paper, we present work on understanding Vietnamese sign language through the use of Micro Electronic Mechanical System (MEMS) accelerometers. The system consists of six ADXL202 accelerometers for sensing the hand posture, a BASIC Stamp microcontroller and a PC for data acquisition and recognition of sign language. The data is then transformed to relative angles between fingers and the p...

Object classification is an important step in visual recognition and semantic analysis of visual content. In this paper, we propose a method for classification of objects that is invariant to illumination color, illumination direction and viewpoint based on 3D color histogram. A 3D color histogram of an image is represented as a 2D image, to capture the color composition while preserving the ne...