Automatic facial feature detection is typically solved by using manually segmented images to train a feature detector. In this paper, we investigate whether it is possible to improve the detection performance of such a feature detector by using additional unsegmented images. We propose a new adaptive automatic facial feature segmentation algorithm which aims to do this. The experimental results...

In this paper, a new methodology is presented for developing a diagnostic system using waveform signals with limited or with no prior fault information. The key issues studied in this paper are automatic fault detection, optimal feature extraction, optimal feature subset selection, and diagnostic performance assessment. By using this methodology, a diagnostic system can be developed and its per...

This paper presents an approach to texture image segmentation using a family of fractional discrimination functions. In contrast to the conventional methods, the proposed functions provide uniform treatment of the existing functions and operators for selective feature extraction. The effectiveness of fractional discrimination functions for texture feature detection is demonstrated in the presen...

A novel generalized feature extraction method based on the Expansion Matching (EXM) method and the Karhunen-Loeve (KL) transform is presented. This yields an eecient method to locate a large variety of features with a single pass of parallel ltering operations. The EXM method is used to design optimal detectors for diierent features. The KL representation is used to deene an optimal basis for r...

In this paper we define a spatial symbolic model that can be used to describe classes of 3-D objects (anatomical and man-made) and a method for finding correspondences between the features of the symbolic models and point sets of 3-D mesh data. An abstract symbolic model is used to describe spatial object classes in terms of parts, boundaries, and spatial associations. A working model is a mech...

The field of optimization and machine learning are increasingly interplayed and optimization in different problems leads to the use of machine learning approaches‎. ‎Machine learning algorithms work in reasonable computational time for specific classes of problems and have important role in extracting knowledge from large amount of data‎. ‎In this paper‎, ‎a methodology has been employed to opt...

Many health problems are generally caused by unhealthy behaviours that occur whilst conducting everyday Activities of Daily Living (ADL), such as poor use of sanitation and hygiene. This paper describes the development of an ADL inference engine, which is able to recognise natural hygiene behaviour patterns. As opposed to traditional ADL classification approaches, the developed inference engine...

We present a probabilistic approach to the discrimination between textured areas and edges; locally defined probabilistic models are used, which model textured areas as sinusoidal and edges as phase-congruent signals. We build a link with energy-based feature detection and propose a simple approach to the discrimination between these two classes. This facilitates the selective use of texture/ed...

This thesis takes researches on the immune intrusion detection and IP trace back technology. To find out the network data features of the real-time analyses, the distributed immune intrusion detection system and the packet marking theory are used; to guide the dynamically processing of path signs technology, the immune intrusion detection system is used; what’s more, to dynamically adaptive dif...